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The Ultimate Guide to Getting Your Thesis Published in a Journal

• 7-minute read
• 25th February 2023

Writing your thesis and getting it published are huge accomplishments. However, publishing your thesis in an academic journal is another journey for scholars. Beyond how much hard work, time, and research you invest, having your findings published in a scholarly journal is vital for your reputation as a scholar and also advances research findings within your field.

This guide will walk you through how to make sure your thesis is ready for publication in a journal. We’ll go over how to prepare for pre-publication, how to submit your research, and what to do after acceptance.

Pre-Publication Preparations

Understanding the publishing process.

Ideally, you have already considered what type of publication outlet you want your thesis research to appear in. If not, it’s best to do this so you can tailor your writing and overall presentation to fit that publication outlet’s expectations. When selecting an outlet for your research, consider the following:

●  How well will my research fit the journal?

●  Are the reputation and quality of this journal high?

●  Who is this journal’s readership/audience?

●  How long does it take the journal to respond to a submission?

●  What’s the journal’s rejection rate?

Once you finish writing, revising, editing, and proofreading your work (which can take months or years), expect the publication process to be an additional three months or so.

Revising Your Thesis

Your thesis will need to be thoroughly revised, reworked, reorganized, and edited before a journal will accept it. Journals have specific requirements for all submissions, so read everything on a journal’s submission requirements page before you submit. Make a checklist of all the requirements to be sure you don’t overlook anything. Failing to meet the submission requirements could result in your paper being rejected.

Areas for Improvement

No doubt, the biggest challenge academics face in this journey is reducing the word count of their thesis to meet journal publication requirements. Remember that the average thesis is between 60,000 and 80,000 words, not including footnotes, appendices, and references. On the other hand, the average academic journal article is 4,000 to 7,000 words. Reducing the number of words this much may seem impossible when you are staring at the year or more of research your thesis required, but remember, many have done this before, and many will do it again. You can do it too. Be patient with the process.

Additional areas of improvement include>

·   having to reorganize your thesis to meet the section requirements of the journal you submit to ( abstract, intro , methods, results, and discussion).

·   Possibly changing your reference system to match the journal requirements or reducing the number of references.

·   Reformatting tables and figures.

·   Going through an extensive editing process to make sure everything is in place and ready.

Identifying Potential Publishers

Many options exist for publishing your academic research in a journal. However, along with the many credible and legitimate publishers available online, just as many predatory publishers are out there looking to take advantage of academics. Be sure to always check unfamiliar publishers’ credentials before commencing the process. If in doubt, ask your mentor or peer whether they think the publisher is legitimate, or you can use Think. Check. Submit .

If you need help identifying which journals your research is best suited to, there are many tools to help. Here’s a short list:

○  Elsevier JournalFinder

○  EndNote Matcher

○  Journal/Author Name Estimator (JANE)

○  Publish & Flourish Open Access

·   The topics the journal publishes and whether your research will be a good fit.

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·   The journal’s audience (whom you want to read your research).

·   The types of articles the journal publishes (e.g., reviews, case studies).

·   Your personal requirements (e.g., whether you’re willing to wait a long time to see your research published).

Submitting Your Thesis

Now that you have thoroughly prepared, it’s time to submit your thesis for publication. This can also be a long process, depending on peer review feedback.

Preparing Your Submission

Many publishers require you to write and submit a cover letter along with your research. The cover letter is your sales pitch to the journal’s editor. In the letter, you should not only introduce your work but also emphasize why it’s new, important, and worth the journal’s time to publish. Be sure to check the journal’s website to see whether submission requires you to include specific information in your cover letter, such as a list of reviewers.

Whenever you submit your thesis for publication in a journal article, it should be in its “final form” – that is, completely ready for publication. Do not submit your thesis if it has not been thoroughly edited, formatted, and proofread. Specifically, check that you’ve met all the journal-specific requirements to avoid rejection.

Navigating the Peer Review Process

Once you submit your thesis to the journal, it will undergo the peer review process. This process may vary among journals, but in general, peer reviews all address the same points. Once submitted, your paper will go through the relevant editors and offices at the journal, then one or more scholars will peer-review it. They will submit their reviews to the journal, which will use the information in its final decision (to accept or reject your submission).

While many academics wait for an acceptance letter that says “no revisions necessary,” this verdict does not appear very often. Instead, the publisher will likely give you a list of necessary revisions based on peer review feedback (these revisions could be major, minor, or a combination of the two). The purpose of the feedback is to verify and strengthen your research. When you respond to the feedback , keep these tips in mind:

●  Always be respectful and polite in your responses, even if you disagree.

●  If you do disagree, be prepared to provide supporting evidence.

●  Respond to all the comments, questions, and feedback in a clear and organized manner.

●  Make sure you have sufficient time to make any changes (e.g., whether you will need to conduct additional experiments).

After Publication

Once the journal accepts your article officially, with no further revisions needed, take a moment to enjoy the fruits of your hard work. After all, having your work appear in a distinguished journal is not an easy feat. Once you’ve finished celebrating, it’s time to promote your work. Here’s how you can do that:

●  Connect with other experts online (like their posts, follow them, and comment on their work).

●  Email your academic mentors.

●  Share your article on social media so others in your field may see your work.

●  Add the article to your LinkedIn publications.

●  Respond to any comments with a “Thank you.”

Getting your thesis research published in a journal is a long process that goes from reworking your thesis to promoting your article online. Be sure you take your time in the pre-publication process so you don’t have to make lots of revisions. You can do this by thoroughly revising, editing, formatting, and proofreading your article.

During this process, make sure you and your co-authors (if any) are going over one another’s work and having outsiders read it to make sure no comma is out of place.

What are the benefits of getting your thesis published?

Having your thesis published builds your reputation as a scholar in your field. It also means you are contributing to the body of work in your field by promoting research and communication with other scholars.

How long does it typically take to get a thesis published?

Once you have finished writing, revising, editing, formatting, and proofreading your thesis – processes that can add up to months or years of work – publication can take around three months. The exact length of time will depend on the journal you submit your work to and the peer review feedback timeline.

How can I ensure the quality of my thesis when attempting to get it published?

If you want to make sure your thesis is of the highest quality, consider having professionals proofread it before submission (some journals even require submissions to be professionally proofread). Proofed has helped thousands of researchers proofread their theses. Check out our free trial today.

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• Publication Process

How to Write a Journal Article from a Thesis

• 3 minute read
• 202.4K views

Table of Contents

You are almost done with your PhD thesis and want to convert it into a journal article. Or, you’re initiating a career as a journal writer and intend to use your thesis as a starting point for an article. Whatever your situation, turning a thesis into a journal article is a logical step and a process that eventually every researcher completes. But…how to start?

The first thing to know about converting a thesis into a journal article is how different they are:

Thesis Characteristics:

• Meets academic requirements
• Reviewed by select committee members
• Contains chapters
• Lengthy, no word limits
• Table of contents
• Lengthy research of literature
• IRB approval described in detail
• Description and copies of tools used
• All findings presented
• Verb tenses may vary

Journal Article Characteristics:

• Meets journalistic standards
• Reviewed by a panel of “blind” reviewers
• Word limits
• Manuscript format
• Succinct research of literature
• IRB described in 1 to 3 sentences
• Essential and succinct tool information
• Selected findings presented
• Verb tenses are fairly consistent

Converting your thesis to a journal article may be complex, but it’s not impossible.

A thesis is a document of academic nature, so it’s more detailed in content. A journal article, however, is shorter, highlighting key points in a more succinct format. Adapting a thesis for conversion into a journal article is a time-consuming and intricate process that can take you away from other important work. In that case, Elsevier’s Language Editing services may help you focus on important matters and provide a high-quality text for submission in no time at all.

If you are going to convert a thesis into a journal article, with or without professional help, here is a list of some of the steps you will likely have to go through:

1. Identify the best journal for your work

• Ensure that your article is within the journal’s aim and scope. How to find the right journal? Find out more .
• Check the journal’s recommended structure and reference style

2. Shorten the length of your thesis

• Treat your thesis as a separate work
• Paraphrase but do not distort meaning
• Select and repurpose parts of your thesis

3. Reformat the introduction as an abstract

• Shorten the introduction to 100-150 words, but maintain key topics to hold the reader’s attention.
• Use the introduction and discussion as basis for the abstract

4. Modify the introduction

• If your thesis has more than one research question or hypothesis, which are not all relevant for your paper, consider combining your research questions or focusing on just one for the article
• Use previously published papers (at least three) from the target journal as examples

5. Tighten the methods section

• Keep the discussion about your research approach short

6. Report main findings in the results

• Expose your main findings in the results section in concise statements

7. Discussion must be clear and concise

• Begin by providing an interpretation of your results: “What is it that we have learned from your research?”
• Situate the findings to the literature
• Discuss how your findings expand known or previous perspectives
• Briefly present ways in which future studies can build upon your work and address limitations in your study

8. Limit the number of references

• To choose the most relevant and recent
• To format them correctly
• Consider using a reference manager system (e.g. Mendeley ) to make your life easier

If you are not a proficient English speaker, the task of converting a thesis into a journal article might make it even more difficult. At Elsevier’s Language Editing services we ensure that your manuscript is written in correct scientific English before submission. Our professional proofers and editors check your manuscript in detail, taking your text as our own and with the guarantee of maximum text quality.

Language editing services by Elsevier Author Services:

• Research Process

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• Publication Recognition

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How to Convert Your Thesis into a Journal Article?

Table of Contents

“Congratulations, your Thesis has been accepted!”

Upon submitting your thesis, when you hear this statement, your heart must have felt complete feelings of joy and pride. You must be in a self-boasting mode where you finally feel that you have sent your baby to the outside world. However, as time passes by, you will gradually get to know that: the majority of the researchers only prefer to read a 10-15 page paper about the most revolutionary part of your research rather than digging through 500 pages of your book-style thesis.

Welcome to the harsh reality, now. After completing the gigantic task of writing, submitting, and defending your Ph.D. thesis, you get to know that it was not enough. The next pragmatic step you must adopt is converting a few parts of your thesis into a journal article.

You can easily create a few journal articles by scouring through your manuscript. While skimming your thesis manuscript, you will be able to discover that a few chapters can easily be segmented and converted into a journal article. These segmented chapters and the research material you gathered during the research phase can provide you with enough materials to create a few journal articles.

There is much confusion around the conversion of the thesis to a journal article. These confusions range from “what is the need for the conversion of the thesis to an article,” “whether it is legit to do so or not,” to “is converting a thesis to a journal considered a plagiarized source, specifically self-plagiarism?”

Even you must have got these questions. So, let me answer and clear off the doubts over these looming questions contesting within you.

Why Publish Articles from Thesis?

It is pretty well known that a research paper asserts much credibility to the author. So, the easiest way to create your first research paper is through your thesis or dissertation. Besides, you will come across many benefits once you have published the first article from your thesis. These can include:

1) Career Boost

A mere bullet point mentioning you have authored a journal article will be an outstanding achievement and addition to your CV. It generally takes a year or two to complete a thesis. Since you have already done the research, you do not need to conduct new research or collect facts. This way, you can save a significant amount of time and publish your research.

Also, like a cherry on a cake, you can create multiple research papers from your thesis. In this way, you will be way ahead of your peers as by the time they will be able to publish one or two articles, you will already be carrying multiple journal articles in your name.

2) Greater Outreach

What happened to your thesis after submission? Probably nothing more than becoming part of your institutions’ archives. It is the usual case with every thesis in most institutions worldwide. However, if you transform that into a journal article, it reaches a far greater audience, surpassing your institution's internal corridors.

3) Self-satisfaction

You have spent a lot of time and effort in creating your thesis. So why not reward your efforts by transforming your thesis into a journal article that can provide a more significant readership, credibility, and praise for your work. Just put in a last-mile effort and convert your thesis into a few journal articles; you can quickly achieve higher recognition and reputation for your work and even yourself. Also, it can help in enhancing your academic and research writing skills.

Is creating articles from a thesis or dissertation legit?

There are a lot of concerns and misconceptions that cloud scholars when it comes to publishing articles from theses. For example, scholars usually get thoughts like if journal publishers accept something that has already been a part of a thesis or dissertation or creating articles from a thesis might come under the purview of a duplicate submission, self-plagiarism, or copyright issues.

I will not say that these questions are entirely baseless or of fault, but publishing articles from a thesis varies in different contexts. What I can frankly say is that publishers are not entirely against publishing articles that have been generated from a thesis. Follow-through below mentioned reasons to understand this:

i) Theses are not formal publications

Most academic publishers do not consider theses or dissertations as formal publications. Theses are published at the institutional level only for internal scrutiny and a little circulation among fellow scholars.

However, if your institution has published your theses through its online channels, then it is prudent for you to inform the academic publisher about this. Staying transparent about the origin of your manuscript with your publisher is the best way to stay away from any unethical practices. The best solution here is to create a citation article for your thesis.

ii) No Copyright Issues

You are the copyright owner when it comes to your thesis. So, when you publish an article from your thesis, there will be no copyright infringement issues. You can register yourself as a copyrights owner if extra protective. In such a scenario, you can create as many articles as possible, and academic publishers will publish them without worrying over any copyright violation.

iii) Duplication and Self-Plagiarism can be easily eliminated

A journal article can be generated easily from a few thesis chapters. Therefore, a journal article that has originated from a thesis or a dissertation is a part of it and not a copy. Additionally, it undergoes a rigorous peer-review process, bringing many differences between an article and your thesis. No one can charge you for duplicating your thesis for a journal article.

Similarly, you can avoid the traps of self-plagiarism by simply citing your thesis/dissertation in the journal paper. Moreover, you can take advantage of quote blocks in sections where you have directly used the same content verbatim as your thesis.

You should inform the publisher that the article has been scoured from your thesis in all of these cases. Moreover, you should furnish them with a copy of your thesis with all the information, such as where and when it was first published, etc. Staying transparent and open about these things with your editor can turn to your advantage as they may help you understand the procedures to be followed to avoid any ethics violations you may not know at that time.

Tips on How to convert your thesis to a journal article

Before mentioning the tips on generating a journal article from your thesis, it is crucial that you first understand a few contrasting aspects of a journal article and a thesis.

First and foremost, the audience or the readers are very different for both the journal article and the thesis. In the case of a thesis, the audience is the institutional committee that evaluates if your thesis is of quality or not. Whereas, for the journal article, the readers are the scientists or scholars of the same domain looking for theories backed with facts and evidence.

Additionally, a thesis is created to serve the educational purpose of achieving a degree. On the other hand, an academic paper/article is published to achieve professional goals like attaining credibility, reputation, and recognition in the academic domain.

A thesis is presented or the format is quite different from a journal article. Like everybody else, you too must have included all that you knew about the topic in your thesis. The purpose of a thesis is to present all the known facts and evidence to manifest your knowledge about a particular subject. Whereas, in the case of journals, you have to manifest your knowledge about the topic in a shorter and precise format.

While creating your first publication, you must be careful to ensure that it includes a concise literature review, calculated methods and methodology section, only the relevant findings and evidence, and a condensed discussion section.

You must draft your first paper after understanding your audience and their questions once they choose to read your article. Simply put, you must know your audience and the answers they will be expecting from your article.

To create your first article from your thesis, keep the above-discussed points in your thoughts and follow through the below-mentioned elements that you revise and amend as per the publication’s requirements.

1) Words limit

Quite pronounced and known to all that a journal article is of much shorter length than a thesis. While a thesis can be 8000-10000 words covering over 200+pages, a journal article can maximum go up to a few thousand words spanning over 5-7pages. Additionally, this length also varies from domain to domain and topic to topic.

Therefore, you must shorten each section very accurately. You need to trim the paragraphs so that the true essence should not get lost, and there should not be any redundancy, too. You must select the key important topics and include them in your academic paper.

2) Abstract

The abstract is the entry point of your academic paper. Therefore, you need to include and present the exciting points of the topic here but briefly. You need to curate it according to the instructions provided by your target journal. You must enquire and ensure whether they require a structured or unstructured abstract. Moreover, there is a growing trend of graphical and video abstracts.

3) Introduction

While writing the introduction, you must present the gaps in your chosen topic that led to the research. Next, you need to write a concise literature review to bring forth the past works and the new results that you aim to find out. In this section, you must specify the research problem and a background check over that topic.

You must have extensively provided details about your chosen methods and methodology in your thesis. However, you can not do the same here. You need to narrow it down to the methodology section, especially the experiments, surveys, and more you have adopted. You are not supposed to present a detailed discussion around the research methodology approach in the journal articles.

You must be aware that a thesis must contain the details of every result with considerable discussions, whereas a journal only contains the result of the main findings. Therefore, while creating the result sections, ensure that you include the results or the findings that directly answer the research question. Also, you must provide hard evidence to back your results. Moreover, strict adherence to the standards of reporting results has to be followed.

6) Discussion

The discussion section of a journal article is meant to provide a brief interpretation of the results to display your understanding of the topic. Ensure that you keep the discussion section of your journal article clear and cut to the point. Be aware that by providing a discussion section, you demonstrate your interest and speculations in the future direction the research topic will adopt.

7) References

Do not just copy-paste the reference or citation list from your thesis to the article. You need to provide the relevant reference and citations you sought when conducting the research. You must ensure that the reference list you are putting here should be relevant to the topic. Sometimes, the academic publishers limit the number of references you can include, so properly enquire beforehand only over the number of references.

Final Words

Publishing articles from the thesis is nowhere prohibited. In reality, if you discuss this idea with your peers, they will encourage you to do it. Just keep in mind the concept of thesis and journal articles, their differences, and the purpose each serves in a different context; you will be able to publish an article from your thesis easily.

The above tips are intended to provide you with a direction to publish articles from your thesis. If you feel overwhelmed by the publisher's requirements or get confused and seek answers, you can come over to the SciSpace (Formerly Typeset) Community. Just submit your questions there, and you will find answers pouring in from experts all over the world. Even now, if you feel that there are certain aspects that this article did not cover, feel free and post your question in the SciSpace Community, and I will make sure that you get your answers ASAP.

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Publishing a Master’s Thesis: A Guide for Novice Authors

Robert g. resta.

1 Swedish Cancer Institute, Swedish Medical Center, Seattle, WA USA

Patricia McCarthy Veach

2 Department of Educational Psychology, University of Minnesota, Minneapolis, MN USA

Sarah Charles

3 Jefferson Kimmel Cancer Center, Thomas Jefferson University Hospital, Philadelphia, PA USA

Kristen Vogel

4 Center for Medical Genetics, NorthShore University HealthSystem, Evanston, IL USA

Terri Blase

5 Department of Maternal Fetal Medicine, Advocate Christ Medical Center, Oak Lawn, IL USA

Christina G. S. Palmer

6 Department of Psychiatry & Biobehavioral Sciences, UCLA, Los Angeles, CA USA

7 Department of Human Genetics, UCLA, Los Angeles, CA USA

8 UCLA Semel Institute, 760 Westwood Plaza, Room 47-422, Los Angeles, CA 90095 USA

Publication of original research, clinical experiences, and critical reviews of literature are vital to the growth of the genetic counseling field, delivery of genetic counseling services, and professional development of genetic counselors. Busy clinical schedules, lack of time and funding, and training that emphasizes clinical skills over research skills may make it difficult for new genetic counselors to turn their thesis projects into publications. This paper summarizes and elaborates upon a presentation aimed at de-mystifying the publishing process given at the 2008 National Society of Genetic Counselors Annual Education Conference. Specific topics include familiarizing prospective authors, particularly genetic counseling students, with the basics of the publication process and related ethical considerations. Former students’ experiences with publishing master’s theses also are described in hopes of encouraging new genetic counselors to submit for publication papers based on their thesis projects.

Introduction

Scholarship is important for growth of a profession and for clinical care. For these reasons, the American Board of Genetic Counseling (ABGC) endorses scholarly activities through Practice Based Competency IV.5 (American Board of Genetic Counseling 2009 ). Boyer ( 1990 ) describes four types of scholarship (Scholarship of Discovery, Scholarship of Integration, Scholarship of Application, and Scholarship of Teaching), all of which are endorsed by ABGC and required of accredited genetic counseling training programs. The first three types of scholarship, which involve generating new knowledge or applying existing knowledge to an important problem, are the basis of the ABGC’s requirement that students in accredited programs engage in scholarship and complete a scholarly product. The ABGC defines a scholarly product to include: a master’s thesis, an independent research project, a literature review/case report, a formal needs assessment, design and implementation of an innovative patient, professional, or community educational program, and/or preparation of a grant proposal.

The purpose of this article is to encourage students to disseminate their scholarly work (except grant proposals) through a journal publication. This article was developed from an Educational Breakout Session (EBS) at the 2008 National Society of Genetic Counselors (NSGC) Annual Education Conference and draws upon the experiences of a past editor and current assistant editor of the Journal of Genetic Counseling ( JOGC ), a student mentor, and recent genetic counseling graduates who successfully turned their student thesis projects into peer-reviewed publications.

Engaging in scholarship is important for increasing genetic counselors’ self-knowledge, but dissemination of scholarship is essential for the growth of the genetic counseling field. McGaghie and Webster ( 2009 ) identify a wide range of types of scholarly products that promote broad dissemination of information, including peer-reviewed journal articles (e.g., original research, case reports, review articles), book chapters, books or monographs, edited books, essays, editorials, book reviews, letters, conference reports, educational materials, reports of teaching practices, curriculum description, videos, simulations, simulators, and web-based tutorials. As evidence of the importance of disseminating scholarship to the field of genetic counseling, dissemination of scholarly products is actively promoted by the NSGC, the major professional organization for the genetic counseling profession. A prominent example of NSGC’s commitment to dissemination is the JOGC , a professional journal devoted to disseminating peer-reviewed information relevant to the practice of genetic counseling. The success of this journal over nearly two decades is a strong indicator of the value genetic counselors place on publishing journal articles as an essential product of scholarship.

Individuals who have completed a master’s thesis or equivalent should consider publication. This “call to publish” student work is based on evidence that a large proportion of students engage in a scholarly activity with publication potential. A recent survey of 531 genetic counselors suggests that 75% of respondents fulfilled their scholarly activity requirement via a master’s thesis (Clark et al. 2006 ). Among this group, 21% classified their thesis as “hypothesis driven” and 20% classified it as a “descriptive study.” Although the research may be relatively small scale given the time and resource constraints of short training programs (≤2 years), it nonetheless offers a rich and varied source of information about the practice of genetic counseling that could be shared with the broader community through publication. Yet Clark et al. ( 2006 ) found that only 21.6% of respondents who completed a master’s thesis had submitted a manuscript for publication in a peer-reviewed journal. It appears that many students do not submit their research for professional publication, perhaps due to a combination of time constraints, lack of mentoring and support, unfamiliarity with the publication process, lack of professional confidence, and fear of rejection (Clark et al. 2006 ; Cohen et al. 2008 ; Driscoll and Driscoll 2002 ; Keen 2006 ). Because this is one aspect of scholarship that has received limited attention, guidance regarding the details and vicissitudes of the publication process, and acknowledgement that master’s theses can be successfully published, are needed.

Of course, one might question why students should or would publish the results of their graduate work. The answer is complex, without a “one size fits all,” because scholarship can be intrinsically and/or extrinsically motivated. McGaghie and Webster ( 2009 ) describe intrinsic motives as including sharing knowledge, career advancement, status improvement, collegial approval, personal pleasure, and response to challenge; extrinsic motives include academic pressure, commitment to patient care, practice improvement, and promoting the use of new technologies. Although the reasons genetic counselors publish articles have not been empirically evaluated, Clark et al. ( 2006 ) (i) concluded that a substantial number of genetic counselors consider active involvement in research (a form of scholarship and precursor to publication) to be a core role, and (ii) found that respondents endorsed a range of intrinsic and extrinsic motives for their involvement in research. These reasons included interest in the subject, contributing to the field, personal development/satisfaction, diversifying job responsibilities, job requirements, lack of existing research on a particular topic, and career advancement. It is reasonable to infer that these reasons would extend to publication as well.

The work that culminates in a master’s thesis provides the basis for a professional journal article. However, writing a professional journal article differs from writing a master’s thesis. This article, therefore, provides practical ideas and considerations about the process for developing a master’s thesis into a peer-reviewed journal article and describes successful case examples. Research and publication occur in stages and include many important topics. Previous genetic counseling professional development articles have partially or comprehensively addressed the topics of developing and conducting a research project (Beeson 1997 ), writing a manuscript (Bowen 2003 ), and the peer-review process (Weil 2004 ). This paper expands on previous articles by describing the publication process and discussing publication ethics, with emphasis on aspects pertinent to publishing a master’s thesis. It is hoped that this article will encourage genetic counselors to publish their research.

The primary audience for this article is genetic counselors who are conducting a master’s thesis or equivalent or who completed a thesis in the last few years which remains unpublished. The secondary audience is other novice authors and affiliated faculty of genetic counseling training programs. Although the focus of this paper is on journal publications which are subject to a peer-review process (e.g., original research, clinical reports, and reviews), some of the basic information applies to a variety of publishing forms.

The Publication Process

Publish before it perishes.

Like produce and dairy products, data have a limited shelf life. Research results may be rendered marginal by new research, social changes, and shifts in research trends. For example, a study of patient reluctance to undergo genetic testing due to concerns about health insurance discrimination conducted in December 2007 would have been obsolete when the Genetic Information Nondiscrimination Act (Pub.L. 110–233, 122 Stat. 881, enacted May 21, 2008) was enacted 5 months later. Or studies of whether patients think they might undergo testing if a gene for a particular condition were identified become less relevant once the gene is actually mapped and sequenced.

The hardest part about writing is actually writing. Making the time to sit down and compose a report of research findings is a very difficult first step. As noted in the three case examples, this is particularly true for a recent graduate whose time is occupied with searching for a new job, moving to a new city, and learning the details of a new job. However, the longer you wait, the more difficult it becomes, and the greater the risk that your data will grow stale. If you do not write it, the paper will likely not get written. The three case examples identify strong mentorship, ongoing communication with co-authors, constructive criticism, and commitment to publication by every author as key elements for successfully preparing a manuscript. The following sections describe basic processes for preparing a paper. See also Table  1 for helpful references about technical aspects of manuscript preparation.

Table 1

Selected Resources For Manuscript Preparation

Choosing a Journal

Research delivered to an inappropriate audience is ignored. Many journals publish genetic counseling research—as demonstrated by the three case examples—and therefore, choosing the right journal is critical (Thompson 2007 ). The first step is to decide who the audience should be. Is it important to reach genetic counselors? Medical geneticists? Or is the audience outside of the genetic counseling community? Some genetic counseling research is of interest to researchers in patient education, decision-making, or the social sciences. Clinicians such as surgeons, radiology technicians, psychologists, and family practice physicians might benefit from a greater understanding of genetic counseling and how it interfaces with their specialties.

The next step is to decide whether the journal is interested in the type of research conducted. For example, does the journal publish articles mostly on medical and clinical issues? Does it publish qualitative research? A description of the scope, aims, and types of research that are published is located in the “Instructions to Contributors” section on the web page of most journals. A look at the journal’s editorial board might also provide a good idea of a journal’s theoretical approaches, philosophical orientation, and research interests. Another strategy is to contact the journal’s editor or a member of the editorial board prior to submitting a manuscript to discuss the appropriateness of the manuscript for the journal. Many editors welcome such pre-submission contact since it reduces their workload of reading inappropriate manuscripts.

A journal’s “impact factor” may be important to some authors when considering where to publish a manuscript. The impact factor is a—perhaps imperfect—statistical measure of a journal’s importance. The impact factor was developed in the early 1960s by Eugene Garfield and Irving Sher and is technically defined as A/B, where A = the number of times articles published in that journal were cited and B = the number of citable articles published by the journal (letters and editorials are not usually citable articles) (Garfield 1994 ). An impact factor of one indicates that on average, articles published in the journal were cited once by other authors.

A journal’s impact factor can vary greatly from year to year, and its practical utility is widely debated (Andersen et al. 2006 ; Chew et al. 2006 ; Greenwood 2007 ; Ha et al. 2006 ; The PLoS Medicine Editors 2006 ). Genetic counselors often publish small studies and case reports. The journals that might publish such papers usually have impact factors of ten or less. Thus the impact factor may be a less important consideration for many genetic counselors when deciding where to publish.

A publisher’s copyright policy may also influence the choice of where to publish. The majority of publishers own the copyright (United States Copyright Office 2008 ) and authors do not have the right to copy, re-use, or distribute their own publications without buying reprints, which can be a significant source of income for publishers. Some journals, like the Public Library of Science (PLoS), are completely Open Access and make all articles fully available online. Other journals have Delayed Open Access, which makes articles publicly available after a specified period of time, often a year or two. Many journals, such as the JOGC , promote Hybrid Open Access in which authors, for a fee, can make their articles publicly available. Some journals will make select articles publicly available, usually those that attract media attention. For grant-funded research, consider the requirements of the funding source; some granting agencies require that the research results be made publicly available at some point.

Peer Review

Peer review is the process in which two or three experts evaluate a manuscript to determine whether it is worthy of publication. Peer review is the backbone of scholarly publishing; no research manuscript gets published until a team of reviewers and journal editors vets it. Ideally, reviewers are objective, constructively critical, open-minded, fair, and insightful. Some journals blind the reviewer to the author’s identity, in hopes that the authors’ reputations or professional relationships will not influence the review. Some journals will let authors suggest reviewers or request that certain people not review a manuscript. A journal’s peer review policies may be another important consideration in choosing where to submit a manuscript.

In practice, peer review is not always ideal (Benose et al. 2007 ; Curfman et al. 2008 ; Hames 2007 ; Wager et al. 2006 ). Nonetheless, no better or viable alternative has been proposed. Reviews may sometimes appear to be arbitrary, unfair, and poorly performed. Reading such reviews can be very difficult and frustrating, even for experienced authors. However, it is a reviewer’s job to be critical, and there may be elements of truth in even the most negative reviews. Some editors may be willing to send a manuscript to another reviewer if an original reviewer produces a harshly critical or poorly thought out critique. Some journals have a formal appeals process if a manuscript is rejected or an author feels a review is inaccurate, inappropriate, or biased. However, sometimes it is simply easier to submit the manuscript to a different journal. Case # 2 describes a successful example where submitting a manuscript to a different journal led to publication.

The manuscript rejection rate varies widely across journals, but about half of all manuscripts are rejected or require significant revisions (Armstrong et al. 2008 ; Hall and Wilcox 2007 ; Liesegang et al. 2007 ). About half of rejected manuscripts are published in other journals (Armstrong et al. 2008 ; Hall and Wilcox 2007 ; Liesegang et al. 2007 ). Even among articles that are accepted for publication, the vast majority will require significant revisions. All three case examples describe manuscripts that underwent significant revision. Thus, prospective authors should not be disheartened if a manuscript is rejected or needs extensive re-writing; this is the rule rather than the exception . Many editors are willing to work with authors who have questions about specific comments or how best to incorporate the reviewers’ suggestions. Busy journal editors would rather answer questions up front than have to laboriously edit a revised manuscript and send it back for further revisions.

Peer review, and the subsequent manuscript revisions, along with the number of manuscripts submitted to the journal, are probably the most critical bottlenecks in determining how long it takes before a manuscript appears in print. Typically, a year or more may pass from the time of submission to the publication date. The three case examples include their timeframes to highlight the need for perseverance and patience with the publication process.

The clearest way for authors to respond to editors’ and reviewers’ comments is to prepare a table that lists each comment and how the authors addressed them, item by item. Some reviewers’ comments may be inaccurate or simply unrealistic (e.g. “The authors should re-do the entire research study...”); these can be discussed in the table or in the cover letter that accompanies the table. Additional information about the peer-review process can be found in Weil ( 2004 ).

Acceptance!

Once a manuscript is accepted for publication, the publisher or the journal editor will send a copyright transfer statement that spells out ownership of the article. This statement must be signed and returned in short order before the manuscript will be published. The corresponding author will receive page proofs, usually electronically, which must be read by the author for accuracy and returned fairly quickly (usually 2–3 days). Many publishers are reluctant to make significant changes in the page proofs, and they may charge for substantial revisions. Thus, the version of the manuscript that is submitted to the journal before the page proofs are generated should be very close to what the author wishes to see in print. Usually at this time publishers will offer the author the option to purchase reprints to allow the author to share the publication with other researchers, co-authors, and colleagues. Some journals will provide a limited number of free reprints or a complimentary copy of the issue of the journal in which the paper appears. The steps in the publication process are summarized in Table  2 .

Table 2

Steps in the Publication Process

a ∼50% of manuscripts are rejected or require significant revision before being accepted for publication

Ethics of Publishing

“Scholarship (like life) is not always fair or precise.” (Thompson 1994 )

Manuscript preparation and submission for publication can be complicated by ethical issues. Many authors may not be aware of these ethical conundrums, let alone have a plan for addressing them. Ethics is not a stagnant concept. As research methodologies and research questions evolve, new ethical issues in publishing arise. This section contains a description of several issues broadly relevant to the publishing practice of genetic counselors, particularly as students or recent graduates. However, it is important for genetic counselors-as-authors to keep abreast of ethical issues relevant to their own work.

“Ethics” are principles that govern the behavior of individuals or groups (Merriam-Webster 1974 ). Ethical codes of conduct exist in order to preserve the integrity of a profession, ensure the public’s welfare, and protect scholars. Ethical issues particularly relevant to writing for publication, include: (1) authorship determination, (2) disclosure and conflicts of interest, (3) plagiarism, (4) subject confidentiality, (5) accuracy of information, and (6) publishing in multiple sources.

Authorship Determination

Consider the following situation: A student conducted an excellent study for her master’s thesis project. At the beginning of the project, her supervisor promised her that she would have first authorship on any manuscripts based on the project. However, when the time came to write the paper, the student procrastinated. Finally, after the supervisor repeatedly “nagged” her, she submitted a draft to her, but it was very poorly written. The supervisor decided the only way to salvage the paper was to totally rewrite it herself. Now the supervisor thinks that she deserves to be the first author. Is this ethical? Does it matter if the project was the student’s master’s thesis rather than a project in which she was voluntarily involved? Are there guidelines that might be implemented in advance to handle this kind of situation?

This complex situation may be all too familiar for many supervisors and students. It raises issues about valuing contributions to the publication process, the power differential between supervisors and students, determining when renegotiation of authorship is warranted, and setting expectations and priorities up front. Whenever manuscripts are authored by more than one individual, order of authorship should be negotiated as early in the process as possible. Only individuals who have actually contributed to the work should be listed as authors. Their order should indicate “...the relative scientific or professional contributions of the individuals involved, regardless of their status” (Shadish 1994 ) (p. 1096). In the sciences, the first and last authors typically are the individuals that made the greatest contributions to the project (Laflin et al. 2005 ). Many journals require a listing of each author’s contribution to the manuscript in order to make sure each person meets the journal’s requirements to be listed as an author.

Student authors pose a special situation. Doctoral students usually are the first authors of papers based on their dissertation research (Nguyen and Nguyen 2006 ). Authorship order is less clear for masters’ projects because masters’ students may lack sufficient knowledge and skills to conduct a project and prepare a manuscript of publishable quality without considerable input from their supervisor (Shadish 1994 ). Thompson ( 1994 ) recommends that when there is any question as to who made the primary contribution, the student should receive higher authorship. His recommendation helps to protect the person who has less power in the situation. Often students are involved in studies that are not based on their own master’s or doctoral research, but rather are connected to an existing research program, such as case examples 1 and 2. In those situations, some authors contend that their involvement should be creative and intellectual in order to warrant authorship; otherwise, student input can be credited in an acknowledgement section (Fine and Kurdek 1993 ; Holaday and Yost 1995 ; Thompson 1994 ).

Negotiating authorship is an important step that should begin in the initial stages of a project. This step usually involves assessing and agreeing upon each person’s tasks, contributions, and efforts. The amount of supervision required for an individual’s contributions is usually considered as well (Fine and Kurdek 1993 ). Sometimes renegotiation of authorship order is necessary due to unexpected changes and/or substantial revision of the manuscript. The key is to remember that authorship is negotiated. Questions to consider throughout this negotiation process include: Who had the original idea for the basis of the publication? Who designed and conducted the study that generated the data? Who will write most of the first draft of the paper? Is the study part of someone’s research lab? Students should maintain early and on-going communication with their co-authors about their investment of time and efforts and the outcomes of those efforts (Sandler and Russell 2005 ). However, scholarly contribution is more important than actual time and effort expended when determining authorship. For more information regarding authorship determination, it may be useful to review guidelines for discussing and clarifying authorship order (Gibelman and Gelman 1999 ) or developing individualized contracts for research collaboration (Stith et al. 1992 ). These guidelines also may be useful for initiating discussion of authorship as part of the curriculum in genetic counseling training programs.

Take another look at the authorship scenario. At the time of the original negotiation of authorship, it is likely that the supervisor (and other parties) believed the student warranted first authorship due to her creative contributions and time allotted to the study. In most authors’ minds, first authorship is equated with substantial contribution to writing the manuscript, usually the first draft, so it is important the student understand this is part of the responsibilities of being first author. Typically students have no experience writing a journal article, and so some procrastination is likely. In this scenario, the authorship dilemma may have been averted by having in place a plan to mentor the student, providing support, and delineating a specific process for writing the first draft of the manuscript.

Manuscripts invariably undergo substantial revision as co-authors and reviewers weigh in, so it is not unusual that the supervisor would revise the student’s first draft. This activity does not prima facie warrant a change in authorship order. However, by developing a specific plan to support the student’s writing, it may minimize the extent of the supervisor’s revisions. It is possible, though, that the student’s procrastination and poor writing should initiate a renegotiation of authorship order because the level and nature of her contributions to the work may be changing. The supervisor and student should discuss the reasons for changing authorship order; the supervisor should not unilaterally make this change without discussion. Keep in mind that the bar for changing authorship should be much higher if the paper is based on the student’s master’s thesis than if it is based on a project in which she was voluntarily involved. It is also important to inform students early in the process that most research is a collaborative effort, requiring time, energy, and sometimes funding, and therefore their collaborators have expectations that their contributions will be rewarded through publication. Developing an a priori policy for renegotiation may often reduce misunderstandings and minimize conflict.

Disclosure and Conflicts of Interest

Consider the following situation: A student conducted a study to evaluate a new program that her clinic is offering to its patients. She interviewed ten patients who participated in the program about their experience. Nine of these patients were in general agreement about the value of the program, while the 10th patient was quite negative about her experience. The student’s impression of this patient is that she is a generally negative person. The student believes that the patient came into the program expecting not to like it. Furthermore, the student is concerned her clinic will lose funding for this program if she reports this patient’s responses. The student decides to exclude her data from the paper. Is this decision ethical? Why or why not?

One ethical issue raised in this scenario involves determining when it is appropriate to exclude data points. Data collected from research can be messy, and it is not unusual for some data points to be excluded from analyses. However, there must be an explicit methodology for excluding data points or subjects, and this information usually is reported in the manuscript. Examples for exclusions include: missing data (e.g., a participant did not complete a majority of the items on a questionnaire); measurement error (e.g., the recorded measurement of a biological process or part of the anatomy is simply impossible); small sample sizes (e.g., an insufficient number of individuals from a minority group participated in the research resulting in numbers too small for meaningful analysis). In the scenario described above, the rationale provided for excluding the 10th patient’s experience is not sufficient to warrant exclusion. Instead, it appears that exclusion of this individual is based on a desire to promote the new program in the student’s clinic. In order to eliminate this form of conflict of interest, one could consider involving a clinic outsider in the analysis and interpretation of the data. By including a clinic outsider in the project, editor and reviewer concerns about the integrity of the data, analyses, and conclusions will be allayed.

Most journals provide another “safeguard,” by requiring a statement about possible conflicts of interest. A conflict of interest statement requires the author to acknowledge in writing the nature of any circumstances that might bias the process and/or outcome of their work. For example, any project and published report that might result in direct financial gains for an author(s) should be disclosed to a journal’s editor and to the readership. Examples of possible conflicts of interest include conducting a study of the effectiveness of a genetic test funded by the company that developed and is marketing the test, or a program evaluation study whose outcome would determine the continuation of the investigators/authors’ jobs.

Plagiarism is a familiar concept to most people. Everyone generally understands the importance of “giving credit where credit is due.” Yet, the National Science Foundation estimates that the prevalence of plagiarism may be as high as 50% (Roig 2001 ). Probably many of these incidents are unintentional and/or occur because the authors were unaware of some of the nuances regarding plagiarism. Although there is some variability within and across disciplines about the specific behaviors that constitute plagiarism, there is general agreement about two broad types (Roig 2001 ): cryptamnesia -an individual thinks their idea is original when it actually was presented by someone else previously; and inappropriate paraphrasing —an individual uses another person’s published text without properly citing that use, and/or using their statements with little or no modification. Specific examples of inappropriate paraphrasing include: (1) publishing another person’s work as one’s own; (2) copying part of another author’s paper and claiming it as one’s own; (3) copying text from another source without using quotations marks and without citing that source in the text; (4) paraphrasing text from another source without providing an in-text citation; (5) summarizing material from another source without clearly connecting the summary to that source; and (6) using copyrighted materials without author/publisher permission (East 2006 ; Lester and Lester Jr. 1992 ).

Additional types of plagiarism include ambiguous use of citations. For instance, an individual includes a citation in a paragraph but does not clearly indicate which content in the paragraph is from the cited work. Another type of plagiarism is self-plagiarism . Self-plagiarism occurs when an individual includes published work of their own for which they do not own the copyright (e.g., reprinting a table from one of their previously published papers); repeating verbatim text from a previously published article. Permission to reprint material from the publisher must be obtained.

Plagiarism is a serious ethical breach which can result in a legal penalty. Strategies for avoiding plagiarism include limiting the use of direct quotes; avoiding the use of secondary sources—it is always better to read and cite an original source when available; and restating ideas in one’s own words while providing in-text citation of the work that contains the original ideas (East 2006 ; Lambie et al. 2008 ; Lester and Lester Jr. 1992 ). When in doubt regarding the originality of one’s words, it is best to cite the source(s) on which they are based. In this regard, it may help to bear in mind that readers will assume all words in the paper are the author’s unless the source(s) are cited.

Subject Confidentiality

Published papers must be written in a way that no subjects can be recognized by others without their written consent (Gavey and Braun 1997 ). Given the unique nature of genetics, family members may also need to provide written consent (McCarthy Veach et al. 2001 ). When possible, identifying information should be removed or disguised (e.g., use of pseudonyms) and data based on multiple subjects should be reported in aggregate (group) form. Institutional review boards (IRBs) play a critical role in assuring protection of subject confidentiality. Many journals require authors to indicate either in the paper or a cover letter that they have obtained institutional review board approval to conduct their animal or human subjects study. In some cases, an ethics board may have been consulted regarding ethical dilemmas reported in a clinical paper and this should be acknowledged in the paper.

Accuracy of Information

Authors are responsible for rigorously checking the accuracy of their facts, data, and conclusions. However, despite one’s best efforts, substantial errors sometimes are not discovered until after a paper is published. In that case, the corresponding author should contact the journal immediately and ask that an erratum be published. On a related note, authors have a professional responsibility to make data sets reported in published papers available to other professionals. This practice allows for verification of the findings and conclusions, and it also makes possible research replications and extensions of the original study. The length of time for retaining research records depends on institutional policy and sponsor policy, so it is important to be aware of how these policies apply to the research generated by a master’s thesis. Often institutional review boards require researchers to state how long they will maintain a data set, and the researchers must adhere to that time frame.

Another accuracy issue concerns modifying and reporting the use of published material (e.g., an interview protocol, psychological instrument, curriculum) without clearly describing the precise nature of the modifications. Interpretation of findings and their comparison to other studies using the “same” instrumentation may be severely compromised when an author fails to report modifications. Further, professional courtesy suggests that permission be sought from the author before changing her or his material. Also, use of published material requires crediting the author(s) of that material by including relevant citations.

Publishing in Multiple Sources

In the sciences, a manuscript should not be under review by more than one journal at a time. It is, however, acceptable to submit material for presentation at a conference prior to its actual publication in a journal, as the authors in case examples 1 and 3 did. Some conferences publish proceedings , and some journals will not publish work that is already published in a Proceedings unless the two papers differ substantially. When in doubt, it is good practice to contact a journal’s editor to determine the journal’s policy. Journals typically only publish original work, but on occasion there may be interest in reprinting an article. Reprinting a previously published paper requires written permission from the owner of the publication copyright. As a matter of courtesy, one should also seek the corresponding author’s permission, even if the author does not own the copyright.

Examples of Success

The benefits of sharing knowledge within the medical community and with the public via publication have been delineated. The publication of original work contributes to the advancement of the genetic counseling field overall, and at the individual level, authorship establishes a level of professional credibility, enhancing opportunities for future employability, funding and job satisfaction. The opportunity to develop a genetic counseling master’s thesis into a manuscript should therefore not be overlooked. Below are the personal accounts of three recent graduates who successfully transformed their individual master’s theses into published manuscripts. These examples were not systematically ascertained, and as such, do not necessarily represent all experiences with trying to publish a master’s thesis. These stories provide “first-hand accounts” of the authors’ experiences and, while acknowledging the challenges, demonstrate commitment to publishing their own projects throughout their careers. Table  3 contains a list of helpful hints gleaned from these cases.

Table 3

Helpful Hints for First Time Authors

Case 1: Consider Writing Your Thesis and Journal Article Concurrently

As a result of personal determination, and above all, strong mentorship, I was able to turn my master’s thesis work into a manuscript published in Patient Education and Counseling , titled “Satisfaction with genetic counseling for BRCA1 and BRCA2 mutations among African American women” (Charles et al. 2006 ). My work was a small component of an existing research project being conducted within a university academically affiliated with my genetic counseling training program. The project was an evaluation of the overall effects of “Culturally Tailored vs. Standard Genetic Counseling Protocol” among African American women.

I started by reviewing previous publications this group of researchers had produced and using these as a guide for my first draft, followed by multiple revisions. Approximately 17 months elapsed between first submission and publication. We submitted the manuscript in its original form in May 2005. We received the reviewers’ comments later that summer, and submitted revisions five months later. The article was accepted in that same month, published online five months later and in print seven months after the online version appeared. Shortly after graduating from my program I submitted an abstract of the work to NSGC for presentation at the 2005 Annual Education Conference, and subsequently learned that it was selected for the NSGC Beth Fine Student Abstract award.

My experience may be unusual because I worked on the manuscript and thesis project concurrently. Composing separate but related documents while still juggling second year genetic counseling student responsibilities was certainly a challenge. Preparing a comprehensive thesis project is a very different task than manuscript composition, the latter of which is more focused and narrow in scope. Challenges posed by this concurrent approach included ensuring that text requirements and deadlines specific to each document were met, as well as incorporating and addressing the reviews of both the training program and peer-reviewers. The main benefits of this approach were that I was still in school and therefore geographically close to my mentors, which facilitated ongoing communication throughout the process, and that the manuscript was under review by a journal before I started my new job.

Factors contributing to the successful publication of this project include mentorship, accountability, and commitment to publication by every author. Supportive, constructively critical, and well published, my mentors had high standards and knew the process. Frankly, I did not want to disappoint them. I found setting deadlines and meeting them, along with the accountability of in-person meetings (as opposed to email), to be effective approaches. Finally, publishing the project was a stated goal of the authors at the initiation of the project. I will not claim that the process was easy, but the goal is certainly attainable and worthwhile.

Case 2: You Need Not Publish Every Thesis Finding—Pick The Most Interesting and Relevant

As is the case for many graduate students, the first time I attempted to publish was after I completed my thesis. My thesis concerned the development of a minority research recruitment database and was the result of my graduate research on underserved populations.

Following graduation, I started my first job as a genetic counselor in a new city. During the overwhelming process of adjusting to “my new life,” my thesis advisor asked me to submit a manuscript to the American Journal of Public Health in response to a call for abstracts on genetics topics. Unfortunately, the deadline was only one week away. I scrambled to cut down my lengthy thesis to a reasonable length and submitted it, knowing that it was not my best work given the time constraint. Needless to say, it was rejected.

I decided that before resubmitting the manuscript to a different journal, I would need to take a different approach to the paper, more or less starting over. While my research results were interesting, they were limited in their application. I decided to publish instead on the success of our research initiative, as other researchers could learn from our process. Since I was changing the focus of the manuscript, I had to do an additional literature search and produce much of the writing from scratch. Most of this work had to be completed in my free time. While it was difficult to stay motivated, working on my manuscript when first starting a job was manageable as my caseload was lightest in the beginning. After several weeks of hard work, I submitted the manuscript to Health Promotion Practice .

About one month later, the editor contacted me and asked me to resubmit my manuscript with revisions. Three different reviewers provided feedback. Initially, it was overwhelming to read through their comments and frustrating, particularly when the reviewers contradicted each other. Despite my frustration, with my co-authors’ guidance I forged ahead and resubmitted, only to have the editor and reviewers ask for additional revisions. There were comments from the same three reviewers, however, far fewer in number. Still, I was beginning to think they would never accept the manuscript. I once again called upon my co-authors for guidance and was able to address the reviewers’ comments and resubmit the manuscript once again.

This time when I heard from the editor, the manuscript was finally accepted. What started out as a 120 page thesis ended up being published as an eight page paper (Vogel et al. 2007 ). It took approximately 8 months of writing and revising before the manuscript was finally accepted and an additional year before it came out in print. While the entire process was a true test of patience and determination, it was ultimately worth it. The experience gave me the foundation to carry on my research career and continue to publish successfully.

Case 3: Expectations and Mentorship are Crucial

I defended my thesis, received my Master’s degree, and was about to move back to the Midwest to start my new job as a genetic counselor, but my long “To-Do” list had one remaining item: Publish master’s thesis. I started the initial master’s thesis process with the expectation from one of my thesis advisors, and now a co-author, that research is not “put down and set aside” until published. I never questioned the process; if I was going to work with this advisor, I would be publishing. I was excited to undertake this challenge and impressed by my thesis advisor’s dedication, mentorship, and desire to see our hard work recognized. Nearly two years later, I could proudly say that this expectation, held by all of my thesis advisors and me, was accomplished. The manuscript, published in the JOGC , describes qualitative research regarding communication of genetic test results within a family (Blase et al. 2007 ).

In the beginning, I was unfamiliar with the publication process, but because of the support and guidance of my advisors, I began to learn the process, and so the frustrations and uncertainties were minimal. I also had a great working relationship with my co-authors that included communicating regularly and setting and meeting deadlines. After deciding the JOGC was the most appropriate venue for my research, I spent a good deal of time reducing and reformatting the 80 page thesis to a 20–25 page manuscript to meet the journal’s guidelines. Given the page constraints, this process necessitated determining which data to focus on and re-framing some information to appropriately fit the readers of my selected journal. Conversations with my advisors were instrumental in this phase.

There was nothing quick about publishing my master’s thesis. I graduated in June 2005, received an email shortly thereafter from one of my advisors about how to begin constructing a first draft of a manuscript, and began working on the manuscript in July 2005. I submitted the manuscript to JOGC in May 2006 and subsequently was informed by the editor that based on the reviews, revisions were required before the manuscript could be considered for publication. In September 2006, after two rounds of revisions, my manuscript was accepted, and by June 2007 it was published in the journal.

Although ultimately I was successful in publishing my master’s thesis, the process had its moments of frustration. I remember getting my first round of comments from the reviewers; I thought I was never going to get to the point of publication. My co-authors supported and encouraged me by explaining that revisions are truly part of the process. I was overwhelmed by the reviewers’ list of questions and changes after my initial submission, followed by additional reviews and revisions. Not only did I have to figure out how to keep the manuscript a priority in light of my new job, but I had to weed through and address the reviewers’ comments, and the suggestions of each co-author. The guidance of my thesis advisors, now co-authors, helped me navigate this process.

I have gained much through this experience. The process has opened doors for me including opportunities to work with other professionals with impressive publishing experiences, as well as speaking and poster presentation opportunities at national conferences. I also have greater confidence about the publishing process. What seemed like such a daunting and impossible task is now an attainable outcome. Although my master’s thesis was my most recent publication, the thought of taking on the publication process again is not nearly as intimidating as I once thought.

Publication of original research, clinical experience, and literature reviews are vital to the growth of the genetic counseling field and to the delivery of genetic counseling services. Publishing also promotes personal growth by counting toward maintenance of ABGC-certification as well as establishing the author as a credible and respected authority both within and outside the genetic counseling field. This professional recognition in turn can lead to employment opportunities, speaking engagements, research funding, and career advancement.

Submitting a manuscript for publication also can be an intellectually challenging, emotionally trying, and time-consuming task. But similar to life’s other difficult tasks, the rewards and satisfaction are commensurately great—to see your name in print, have your work cited by other authors, and know that you have contributed in a meaningful way to the practice and understanding of genetic counseling. Transforming a master’s thesis into a journal article is an obvious first step in developing and sustaining a commitment to publishing for our genetic counseling profession. Common themes in the three success experiences include the importance of mentorship and clear expectations for publishing, recognition of the length of the process and concomitant need for perseverance in the face of revisions, awareness of personal and professional benefits in terms of presentations at national meetings, awards, and motivation to continue publishing. Hopefully the information provided in this article will help to de-mystify the publishing process, promote consideration of ethical issues in publishing, and stimulate genetic counseling students and new graduates to embrace a “Publish for Success” philosophy.

Acknowledgments

This paper was developed from an Educational Breakout Session (EBS) sponsored by the Jane Engelberg Memorial Fellowship Advisory Group at the 2008 NSGC Annual Education Conference.

Open Access

This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.

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Research Guides

Submit and publish your thesis.

• The Graduate Thesis: What is it?
• Thesis Defences
• Deadlines and Fees
• Formatting in MS Word
• Formatting in LaTeX
• Making Thesis Accessible
• Thesis Embargo
• Review and Release
• Your Rights as an Author
• Re-using Third Party Materials
• Creative Commons Licenses for Theses
• Turning Thesis into an Article
• Turning Thesis into a Book
• Other Venues of Publication

Publishing from your thesis before or after graduation

"Will repository submission affect my publishing plans?"

... this is a common question for someone looking to publish from their thesis before or after graduation.

Most journals welcome submissions based on a thesis or dissertation. Some may have additional requirements, such as to:

• Let them know about the university’s requirement to make your thesis publicly available
• Submit a manuscript that is substantially different than the thesis content
• Embargo the thesis until after publication, etc.

Your steps will depend on the following scenarios:

Scenario 1 - you ARE NOT planning on publishing your thesis before or after graduation

In this case:

• You can submit your thesis without an embargo
• Your thesis will become publicly available in TSpace  and Library and Archives Canada after your convocation and will be widely indexed via search engines and indexes
• Use the TSpace-generated permanent URL to share and cite your thesis - see example of such citation below

Tajdaran, K. (2015). Enhancement of Peripheral Nerve Regeneration with Controlled Release of Glial Cell Line-derived Neurotrophic Factor (GDNF) (Master’s Thesis, University of Toronto). Retrieved from http://hdl.handle.net/1807/74747

Scenario 2 - You ARE planning on publishing your thesis AFTER graduation

Most journals are interested in “original, previously unpublished” research. Some journals consider theses as a form of “prior publications”, others do not, and the majority does not have a clear definition. It will be best to check journal policy before you submit your thesis.

Nature Research will consider submissions containing material that has previously formed part of a PhD or other academic thesis which has been published according to the requirements of the institution awarding the qualification.

►►►How to check journal policies:

• MIT Libraries' list of policy excerpts from major publishers
• Journal’s website - usually under Information for Authors or Copyright / Permissions or Editorial Policy; or in the publication agreement if available online
• If such information cannot be located online, contact the editors directly
• If the journal requires that you place an embargo on your thesis until after publication, see the SGS instructions on how to request an embargo on your thesis .

Scenario 3 - You ARE planning on publishing (or have already published) from your thesis BEFORE graduation

You may want or be expected to publish parts of your thesis before your thesis is submitted, such as with an integrated/publication-based/sandwich thesis. The most important thing to keep in mind here is copyright. You own copyright of your written materials, and a publisher may require copyright transfer of your manuscript.

You need to ensure you retain certain rights or obtain permission in order to satisfy the university’s requirement of making your thesis openly accessible via TSpace, ProQuest and Library and Archives Canada (LAC). For more details on these repositories, see the  Review and Release  section of this guide.

Check whether the journal requires prior notification about U of T’s open access requirement for theses. Some journals want to be notified of this mandate whether or not they restrict the re-use of articles in theses.

Check whether the publisher requires copyright transfer . This should be stated on their website, in the publication agreement, or you can inquire directly with the journal.

If the publisher does not require copyright transfer , i.e. author retains copyright, then you can reuse your article/chapter in your thesis; no permission needed.

If the publisher requires copyright transfer , follow these steps:

Check if the publisher has special provisions for reusing your published work in your thesis. They may permit the inclusion of a non-final version, such as your submitted or accepted manuscript. See more below on understanding different article versions for sharing .

►►►How to check journal policies:  See MIT Libraries' list of policy excerpts from major publishers or the journal/publisher website.

For example, Taylor and Francis policy allows to:

Include your article Author’s Original Manuscript (AOM) or Accepted Manuscript(AM) , depending on the embargo period in your thesis or dissertation. The Version of Record cannot be used. https://authorservices.taylorandfrancis.com/copyright-and-you/

Check if the article is distributed under a Creative Commons license. This may allow re-use.

►►►How to check journal's CC license:  See the journal/publisher website or contact the journal directly.

If the publisher requires copyright transfer, has no special provisions and does not publish under a CC license, you will need to contact them to request permission to include your article in your thesis. You can:

• Negotiate making the article available as part of the thesis in TSpace, ProQuest, and LAC Theses Portal; 
• Request an embargo [link to Lisa’ section on embargo] if the publisher only permits open sharing after some time post-publication;
• If permission is denied you may include in place of the chapter an abstract and a link to the article on the journal website.

If you have specific questions about your situation, publisher policy or author rights, contact the Scholarly Communications and Copyright Office at [email protected] for a consultation (best before you publish!)

Understanding different versions of a published article

A publisher may distinguish between the versions of an article that you may be allowed to include in your thesis:

• Submitted manuscript / pre-print - version you initially send in (often permitted)
• Accepted manuscript / post-print - version after peer review but before copyediting, layout editing, formatting, etc. (sometimes permitted; publisher may require an embargo/access restriction for a period of time)
• Version of record / final publisher’s PDF - version that appears in the journal (many publishers do not permit sharing this version)

►►►How to check article versions permitted for sharing:

• MIT Libraries’s list of policy excerpts from major publishers
• Sherpa/RoMEO database of publisher policies
• Journal’s website - usually under Information for Authors or Copyright/Permissions or Editorial Policy; or in the publication agreement if available online
• << Previous: Creative Commons Licenses for Theses
• Next: Turning Thesis into an Article >>
• Last Updated: Sep 15, 2023 3:23 PM
• URL: https://guides.library.utoronto.ca/thesis

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• About this guide
• Publishing strategy
• Selecting a journal
• Evaluating journals
• Open Access publishing
• Choose a conference

Publishing from your thesis

Examples of publisher's policies, got invited to publish a book.

• Publishing processes
• Author rights & copyright
• Publishing guidelines

Worried your open access thesis will compromise your article publishing? 

Some researchers may have been questioned or refused acceptance for self-plagiarism. Many publishers use plagiarism checkers like Turnitin on the initial submission and this will find postgraduate theses on Tuwhera.

Consider the following before you submit your articles:

• Check the publisher's policy on their website.
• Check publisher's policy -  this document  lists some key publishers' statements regarding pre-publication and open access theses.
• Whether you are writing a book or an article from your thesis, make sure you have rewritten your research substantially.
• Negotiate an agreement with your publisher to ensure that you are able to use your research in your thesis for your article or book.
• Make sure that you have gained permissions for using any 3rd party copyright materials in your publications.
• Turning your PhD into a successful book Taylor and Francis
• Converting your PhD Thesis into a Book in Five Steps Elsevier Author Services

Some postgraduates may be contacted by "Print on Demand" (POD) publishers offering to publish their research as a book. POD publishers publish theses in a PDF format with an ISBN number. Theses are then listed on Amazon and other bookseller sites. A hard copy is printed when someone makes a request. Typically such emails come from a publisher called VDM (Verlag Dr. Mueller) or any publishing units associated with LAP (Lambert Academic Publishing).

While you own the copyright in your work and are therefore free to decide what to do with it, we advise that you consider these points before proceeding:

• Unlike traditional publishing, the works are not vetted, peer reviewed or professionally edited.
• Your research is already available on Tuwhera, without cost or restriction, for other researchers and students around the world to read.
• You may be asked to sign away the copyright in your own work. Look at the terms and conditions very carefully and consider seeking legal advice before signing.
• Publishing in this way is very likely to harm your chances of publishing your research with a traditional and often more reputable publisher.

In addition to requesting a copy of their author-publisher agreement, here are some things you should try to ascertain before making a decision:

• What is the quality of the printed books (jackets, binding, etc)?
• What is the royalty share you will receive? With POD, as with vanity publishing, you have very little certainty as to the number of books that will be sold.
• What will the publisher do to market/promote your work?
• Will people be able to obtain your thesis only through this publisher from now on? Will they require that your thesis be removed from Tuwhera ?

Vanity Press

The difference between predatory publishers and vanity press. "Predatory publishers claim to have a working peer review, but actually it’s either not present or it’s substantially flawed. Vanity press, on the other hand, never claim to have a peer review process – therefore they are usually perfectly legal businesses." From Bealll's List . Be careful about sending your work to these publishers.

• << Previous: Choose a conference
• Next: Publishing processes >>
• Last Updated: Jan 26, 2024 11:18 AM
• URL: https://aut.ac.nz.libguides.com/getting_published

How to create a journal article from a thesis

Affiliation.

• 1 School of Nursing and Midwifery, University of Queensland, Australia. [email protected]
• PMID: 22866554
• DOI: 10.7748/nr2012.07.19.4.21.c9220

Aim: To identify strategies to assist in the publication of research arising from a postgraduate thesis or dissertation.

Background: There are many benefits to publishing a journal article from a completed thesis, including contributing knowledge to the writer's chosen field, career enhancement and personal satisfaction. However, there are also numerous obstacles for the newly graduated student in crafting an article fit for a specialist publication from a thesis.

Data sources: The author conducted a search of the title, abstract and keywords of the Cinahl, Scopus and Proquest databases, from 1990 to 2010: The author searched for the words: 'journal article' or 'manuscript; 'thesis' or 'dissertation'.

Review methods: The author excluded papers if: they pertained to allocation of authorship to someone other than the academic adviser; related to undergraduate issues rather than graduate dissertations; were discussions of the merits of a PhD by 'publication' instead of 'by thesis'; were not published in a peer-reviewed journal; or were not in English.

Conclusion: The relationship between adviser and student changes as the student becomes a graduate, and new roles for the student and adviser need to be negotiated.

Implications for research/practice: Students need to realise that writing a paper from a thesis is usually going to be more difficult than they anticipate, but the application of strategies discussed in this paper should make the task manageable. Furthermore, universities might wish to consider alternatives in which published papers emerge before the examination of a thesis, such as requiring students to write a paper as part of their coursework.

• Academic Dissertations as Topic*
• Nursing Research*
• Periodicals as Topic*
• Publishing*

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• Research Papers

How to Write and Publish Your Research in a Journal

Last Updated: February 26, 2024 Fact Checked

Choosing a Journal

Writing the research paper, editing & revising your paper, submitting your paper, navigating the peer review process, research paper help.

This article was co-authored by Matthew Snipp, PhD and by wikiHow staff writer, Cheyenne Main . C. Matthew Snipp is the Burnet C. and Mildred Finley Wohlford Professor of Humanities and Sciences in the Department of Sociology at Stanford University. He is also the Director for the Institute for Research in the Social Science’s Secure Data Center. He has been a Research Fellow at the U.S. Bureau of the Census and a Fellow at the Center for Advanced Study in the Behavioral Sciences. He has published 3 books and over 70 articles and book chapters on demography, economic development, poverty and unemployment. He is also currently serving on the National Institute of Child Health and Development’s Population Science Subcommittee. He holds a Ph.D. in Sociology from the University of Wisconsin—Madison. There are 13 references cited in this article, which can be found at the bottom of the page. This article has been fact-checked, ensuring the accuracy of any cited facts and confirming the authority of its sources. This article has been viewed 696,436 times.

Publishing a research paper in a peer-reviewed journal allows you to network with other scholars, get your name and work into circulation, and further refine your ideas and research. Before submitting your paper, make sure it reflects all the work you’ve done and have several people read over it and make comments. Keep reading to learn how you can choose a journal, prepare your work for publication, submit it, and revise it after you get a response back.

Things You Should Know

• Create a list of journals you’d like to publish your work in and choose one that best aligns with your topic and your desired audience.
• Prepare your manuscript using the journal’s requirements and ask at least 2 professors or supervisors to review your paper.
• Write a cover letter that “sells” your manuscript, says how your research adds to your field and explains why you chose the specific journal you’re submitting to.

• Ask your professors or supervisors for well-respected journals that they’ve had good experiences publishing with and that they read regularly.
• Many journals also only accept specific formats, so by choosing a journal before you start, you can write your article to their specifications and increase your chances of being accepted.
• If you’ve already written a paper you’d like to publish, consider whether your research directly relates to a hot topic or area of research in the journals you’re looking into.

• Review the journal’s peer review policies and submission process to see if you’re comfortable creating or adjusting your work according to their standards.
• Open-access journals can increase your readership because anyone can access them.

• Scientific research papers: Instead of a “thesis,” you might write a “research objective” instead. This is where you state the purpose of your research.
• “This paper explores how George Washington’s experiences as a young officer may have shaped his views during difficult circumstances as a commanding officer.”
• “This paper contends that George Washington’s experiences as a young officer on the 1750s Pennsylvania frontier directly impacted his relationship with his Continental Army troops during the harsh winter at Valley Forge.”

• Scientific research papers: Include a “materials and methods” section with the step-by-step process you followed and the materials you used. [5] X Research source
• Read other research papers in your field to see how they’re written. Their format, writing style, subject matter, and vocabulary can help guide your own paper. [6] X Research source

• If you’re writing about George Washington’s experiences as a young officer, you might emphasize how this research changes our perspective of the first president of the U.S.
• Link this section to your thesis or research objective.
• If you’re writing a paper about ADHD, you might discuss other applications for your research.

• Scientific research papers: You might include your research and/or analytical methods, your main findings or results, and the significance or implications of your research.
• Try to get as many people as you can to read over your abstract and provide feedback before you submit your paper to a journal.

• They might also provide templates to help you structure your manuscript according to their specific guidelines. [11] X Research source

• Not all journal reviewers will be experts on your specific topic, so a non-expert “outsider’s perspective” can be valuable.

• If you have a paper on the purification of wastewater with fungi, you might use both the words “fungi” and “mushrooms.”
• Use software like iThenticate, Turnitin, or PlagScan to check for similarities between the submitted article and published material available online. [15] X Research source

• Header: Address the editor who will be reviewing your manuscript by their name, include the date of submission, and the journal you are submitting to.
• First paragraph: Include the title of your manuscript, the type of paper it is (like review, research, or case study), and the research question you wanted to answer and why.
• Second paragraph: Explain what was done in your research, your main findings, and why they are significant to your field.
• Third paragraph: Explain why the journal’s readers would be interested in your work and why your results are important to your field.
• Conclusion: State the author(s) and any journal requirements that your work complies with (like ethical standards”).
• “We confirm that this manuscript has not been published elsewhere and is not under consideration by another journal.”
• “All authors have approved the manuscript and agree with its submission to [insert the name of the target journal].”

• Submit your article to only one journal at a time.
• When submitting online, use your university email account. This connects you with a scholarly institution, which can add credibility to your work.

• Accept: Only minor adjustments are needed, based on the provided feedback by the reviewers. A first submission will rarely be accepted without any changes needed.
• Revise and Resubmit: Changes are needed before publication can be considered, but the journal is still very interested in your work.
• Reject and Resubmit: Extensive revisions are needed. Your work may not be acceptable for this journal, but they might also accept it if significant changes are made.
• Reject: The paper isn’t and won’t be suitable for this publication, but that doesn’t mean it might not work for another journal.

• Try organizing the reviewer comments by how easy it is to address them. That way, you can break your revisions down into more manageable parts.
• If you disagree with a comment made by a reviewer, try to provide an evidence-based explanation when you resubmit your paper.

• If you’re resubmitting your paper to the same journal, include a point-by-point response paper that talks about how you addressed all of the reviewers’ comments in your revision. [22] X Research source
• If you’re not sure which journal to submit to next, you might be able to ask the journal editor which publications they recommend.

Expert Q&A

You might also like.

• If reviewers suspect that your submitted manuscript plagiarizes another work, they may refer to a Committee on Publication Ethics (COPE) flowchart to see how to move forward. [23] X Research source Thanks Helpful 0 Not Helpful 0

• ↑ https://www.wiley.com/en-us/network/publishing/research-publishing/choosing-a-journal/6-steps-to-choosing-the-right-journal-for-your-research-infographic
• ↑ https://link.springer.com/article/10.1007/s13187-020-01751-z
• ↑ https://libguides.unomaha.edu/c.php?g=100510&p=651627
• ↑ http://www.canberra.edu.au/library/start-your-research/research_help/publishing-research
• ↑ https://writingcenter.fas.harvard.edu/conclusions
• ↑ https://writing.wisc.edu/handbook/assignments/writing-an-abstract-for-your-research-paper/
• ↑ https://www.springer.com/gp/authors-editors/book-authors-editors/your-publication-journey/manuscript-preparation
• ↑ https://apus.libanswers.com/writing/faq/2391
• ↑ https://academicguides.waldenu.edu/library/keyword/search-strategy
• ↑ https://ifis.libguides.com/journal-publishing-guide/submitting-your-paper
• ↑ https://www.springer.com/kr/authors-editors/authorandreviewertutorials/submitting-to-a-journal-and-peer-review/cover-letters/10285574
• ↑ http://www.apa.org/monitor/sep02/publish.aspx
• ↑ Matthew Snipp, PhD. Research Fellow, U.S. Bureau of the Census. Expert Interview. 26 March 2020.

About This Article

To publish a research paper, ask a colleague or professor to review your paper and give you feedback. Once you've revised your work, familiarize yourself with different academic journals so that you can choose the publication that best suits your paper. Make sure to look at the "Author's Guide" so you can format your paper according to the guidelines for that publication. Then, submit your paper and don't get discouraged if it is not accepted right away. You may need to revise your paper and try again. To learn about the different responses you might get from journals, see our reviewer's explanation below. Did this summary help you? Yes No

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How to Get Your Thesis Published

Writing a thesis is tough. Current or recent graduate students understand the time and effort required to successfully complete their research program. Indeed, graduate training involves extensive amounts of research that often reflects years of failures and successes. This research often leads to some type of novel insight, which is organized into either a t hesis paper or dissertation.

When writing a dissertation or a thesis , there is much to consider. Both require extensive amounts of work and reflect the years of research conducted by the student. Some universities require that students publish this final research in peer-reviewed journals prior to being considered eligible to graduate. Meanwhile, others do not require the thesis to be officially published. Ultimately, regardless of the graduation requirements, certain career tracks for PhDs or Master’s students require publication in peer-reviewed journals.

Graduate Writing

The type of graduate writing that is required by a student’s university depends upon where the graduate student has studied. In Europe, a doctoral thesis reflects original research, whereas, in the USA, a thesis is often a shorter document associated with a Master’s degree.

Whatever the title, extensive research projects are organized into a final document. Some of these written documents can be formatted into a book. Before publishing, a graduate student should consider several factors prior to publishing. Namely, the student should ask, is my research

• Rigorous: Is it methodical, scholarly work?
• Significant: Why does it matter to your potential audience?
• Original: Is it novel and unique?
• Marketable: Are there potential customers?

When to Publish?

In the past, universities have published theses graduation research summaries in only a hard copy format, such as a bound book. Now, some theses or dissertations are available online, often with a Creative Commons license. This can be a problem due to the requirement by journals that manuscripts contain only unpublished and original data. However, generally, a thesis or dissertation consisting of original, previously unpublished research that has been made available by your home institution does not prevent you from publishing. Rather, journals will consider these theses and dissertations that were published by universities as, understandably, still sufficiently novel data. Furthermore, peer review is an integral component of publication. To pass the muster of peer review, it is important to consider the feedback of dissertation or thesis committee. The critiques of your committee will often mirror the potential concerns of your peer reviewers.

Related: Planning to publish your Ph.D. research in a good journal?  Check these journal selection guidelines now!

Tips and Common Concerns

When going to publish your dissertation, there are generally some common errors made by graduate students.

First, it is generally a good practice to reference or acknowledge the thesis. Since the dissertation may be available publicly, it is important to be transparent about the source of the data.  Similarly, always inform journals that some research contained within a thesis or dissertation was published either in a print-only version or in an online repository.

You can publish your thesis as a monograph or a series of articles. It can depend on the type of thesis.

• Traditional thesis: It is usually in the form of chapters and is an original work written by an individual student.
• Thesis by publication: It consists of papers that have already been published in a journal.

According to COPE guidelines , when thesis contains original unpublished work, it should not be considered as prior publication. Therefore, it is acceptable to be published as a manuscript or a monograph in a journal, even if it is available freely in university repositories and Creative Common license may or may not apply.  However, if the thesis is of the second type, then the papers will be considered as prior publication and are not acceptable as original works for publication. As a research lab hosts student’s work, it is important to first review the policies of your host university. Similarly, since fields transform rapidly, don’t wait too long before publishing. If you do, you run the risk of your literature review or methodology becoming outdated.

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Thesis content and article publishing

Journal publishers usually acquire the copyright to scholarly articles through a publication agreement with the author. Their policies then determine what authors can do with their work.

Below are publisher policies regarding graduate students’ reuse of their previously published articles in their theses, and policies on accepting journal submissions that first appeared in an author’s previously released thesis.

If an article is co-authored with a member of the MIT faculty, or if you have opted-in to an OA license , the MIT open access policy  is likely to apply to the article, which allows for the extension of additional rights to graduate student authors through MIT for reuse.  Short excerpts of published works may also be available for reuse under the MIT Libraries license agreements .

See this page for information about who owns the copyright to your thesis (generally, it’s either MIT or you).

Please contact [email protected] with questions or if you need information that does not yet appear below.

American Association for the Advancement of Science (AAAS)

Reuse of author’s previously published article in author’s thesis

Check the terms of your publication agreement .

Submission of new article by author that first appeared as part of author’s thesis

Allows :  “ We do not regard dissertations/theses as prior publications.”

American Chemical Society

Allows : “Authors may reuse all or part of the Submitted, Accepted or Published Work in a thesis or dissertation that the author writes and is required to submit to satisfy the criteria of degree-granting institutions…. Appropriate citation of the Published Work must be made as follows “Reprinted with permission from [COMPLETE REFERENCE CITATION]. Copyright [YEAR] American Chemical Society.”

“If the thesis or dissertation to be published is in electronic format, a direct link to the Published Work must be included using the  ACS Articles on Request link.”

See also this FAQ for thesis info.

Each ACS journal has a specific policy on prior publication that is determined by the respective ACS Editor-in-Chief. Authors should consult these policies and/or contact the appropriate journal editorial office to ensure they understand the policy before submitting material for consideration.

American Geophysical Union

Allows : “If you wish to reuse your own article (or an amended version of it) in a new publication of which you are the author, editor or co-editor, prior permission is not required (with the usual acknowledgements). However, a formal grant of license can be downloaded free of charge from RightsLink by selecting “Author of this Wiley article” as your requestor type.”

Allows : “Previously published explicitly does not include oral or poster presentations, meeting abstracts or student theses/dissertations.”

American Institute of Aeronautics and Astronautics

Allows : “ Upon publication of an article or paper in an AIAA journal or conference proceeding, authors can use in their own theses/dissertations (with permission of AIAA if required by copyright).”

From here : “In most cases when AIAA is the copyright holder of a work, authors will be automatically granted permission by AIAA to reprint their own material in subsequent works, to include figures, tables, and verbatim portions of text, upon request. Explicit permission should be sought from AIAA through Copyright Clearance Center (CCC) ; all reprinted material must be acknowledged and the original source cited in full.” 

American Institute of Physics

Allows : “A uthors do not need permission from AIP Publishing to reuse your own AIP Publishing article in your thesis or dissertation (please format your credit line: “Reproduced from [FULL CITATION], with the permission of AIP Publishing”)” Author agreement says the version of record can be used . 

Allows : Publishing the work in a thesis is not considered prior publication according to author warranties in the publication agreement.

American Physical Society

Allows , “ provided the bibliographic citation and the APS copyright credit line are given on the appropriate pages.”

Allows Language from Physical Review journals page: “Publication of material in a master’s or doctoral thesis does not preclude publication of that material in the Physical Review journals.”

American Society for Clinical Investigation

After Jan 4, 2022 : “Effective with the January 4, 2022 issue of JCI, authors retain copyright on all articles, which are published with a Creative Commons Attribution License (CC BY 4.0).”

Prior to Jan 4, 2022 : “ Permission can be obtained via Copyright Clearance Center . Copyright or license information is noted on each article.”

Likely allows : D oesn’t explicitly call out theses but says posting on preprints isn’t prior publication. 

Association for Computing Machinery (ACM)

Allows : “Authors can include partial or complete papers of their own (and no fee is expected) in a dissertation as long as citations and DOI pointers to the Versions of Record in the ACM Digital Library are included. Authors can use any portion of their own work in presentations and in the classroom (and no fee is expected).”

Likely allows . Prior publication rules apply to “peer reviewed” publications.  

Cambridge University Press

Allows : “Permissions requests are waived if t he author of the work wishes to reproduce a single chapter (not exceeding 20 per cent of their work), journal article or shorter extract in a subsequent work (i.e. with a later publication date) of which he or she is to be the author, co-author or editor.”

Policies set by individual journals.

Allows : “ ​​ Use and share their works for scholarly purposes (with full acknowledgement of the original article): Include in a thesis or dissertation (provided this is not published commercially).”

Allows : “ Elsevier does not count publication of an academic thesis as prior publication.”

Emerald Publishing

Allows . Authors should use the submitted version or accepted manuscript version.  Use of the final published version is permitted in print, but not electronic versions of theses.

Allows : “We are happy for submissions to Emerald to include work that has previously formed part of your PhD or other academic thesis. Please submit your paper in the usual way but declare the existence of the uploaded thesis to the Editor of the journal. If the Editor wished to consider the paper further, the paper would go through our standard anonymised peer-review process.”

Allows , with some requirements

Theses not specifically addressed , but permitted subject to editorial discretion. Individual journals may have their own policies.

Institute of Physics

Allows. A uthor may use the final published version or figures/text, and should include citation and a link to the version of record. “When you transfer the copyright in your article to IOP, we grant back to you certain rights, including the right to include all or part of the Final Published Version of the article within any thesis or dissertation.”

Inter-Research Science Center

Reuse of published content is “generally free of charge,” but you must get permission. Email: [email protected]

Not addressed , except to say, “ Permission to re-use any previously published material must have been obtained by the authors from the copyright holders.”

International Speech Communication Association (ISCA) INTERSPEECH conference

Allows , with citation. “ISCA grants each author permission to use the article in that author’s dissertation….”

Mathematical Sciences Publishers

Allows , with citation. “The Author may use part or all of this Work or its image in any future works of his/her/their own.”

Unclear, but the author agreement says , “The Author warrants that the Work has not been published before, in any form except as a preprint.” We suggest asking your editor.

National Academy of Sciences

Allows , with citation. “ PNAS authors do not need to obtain permission in the following cases: …to include their articles as part of their dissertations.”

Not addressed . “ What constitutes prior publication…will be determined on a case-by-case basis.

Allows , with citation. “ Authors have the right to reuse their article’s Version of Record, in whole or in part, in their own thesis.”

Allows . “ Nature Portfolio will consider submissions containing material that has previously formed part of a PhD or other academic thesis which has been published according to the requirements of the institution awarding the qualification.”

Oxford University Press

Journals have their own policies . OUP uses the Copyright Clearance Center for permissions . Contact your editor.

Royal Society of Chemistry

Allows , but says, “ Excerpts or material from your dissertation that have not been through peer review will generally be eligible for publication. However, if the excerpt from the dissertation included in your manuscript is the same or substantially the same as any previously published work, the editor may determine that it is not suitable for publication in the journal.”

Allows — in addition, a special agreement with Springer for MIT authors allows for reuse for scholarly and educational purposes.

Policy varies by journal but according to Springer: “There are no overriding ethical issues as long as the dual publication is transparent and cross referenced. Transparency is key, though a few journals might reject such an article for the reason of non-originality.”

Taylor & Francis

Allows — authors retain the right to “Include your article Author’s Original Manuscript (AOM) or Accepted Manuscript(AM), depending on the embargo period, in your thesis or dissertation. The Version of Record cannot be used.”

Allows : “ Y ou may share any version of your article with individual colleagues and students… as submission of thesis, or doctorate.”

Allows : “ The following types of “prior publication” do not present cause for concerns about duplicate or redundant publication: Dissertations and theses in university archives.”

Page last updated: February 8, 2024

Writing a Postgraduate or Doctoral Thesis: A Step-by-Step Approach

• First Online: 01 October 2023

Cite this chapter

• Usha Y. Nayak 4 ,
• Praveen Hoogar 5 ,
• Srinivas Mutalik 4 &
• N. Udupa 6  

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A key characteristic looked after by postgraduate or doctoral students is how they communicate and defend their knowledge. Many candidates believe that there is insufficient instruction on constructing strong arguments. The thesis writing procedure must be meticulously followed to achieve outstanding results. It should be well organized, simple to read, and provide detailed explanations of the core research concepts. Each section in a thesis should be carefully written to make sure that it transitions logically from one to the next in a smooth way and is free of any unclear, cluttered, or redundant elements that make it difficult for the reader to understand what is being tried to convey. In this regard, students must acquire the information and skills to successfully create a strong and effective thesis. A step-by-step description of the thesis/dissertation writing process is provided in this chapter.

• Dissertation
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Nayak, U.Y., Hoogar, P., Mutalik, S., Udupa, N. (2023). Writing a Postgraduate or Doctoral Thesis: A Step-by-Step Approach. In: Jagadeesh, G., Balakumar, P., Senatore, F. (eds) The Quintessence of Basic and Clinical Research and Scientific Publishing. Springer, Singapore. https://doi.org/10.1007/978-981-99-1284-1_48

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• Published: 26 March 2024

Predicting and improving complex beer flavor through machine learning

• Michiel Schreurs   ORCID: orcid.org/0000-0002-9449-5619 1 , 2 , 3   na1 ,
• Supinya Piampongsant 1 , 2 , 3   na1 ,
• Miguel Roncoroni   ORCID: orcid.org/0000-0001-7461-1427 1 , 2 , 3   na1 ,
• Lloyd Cool   ORCID: orcid.org/0000-0001-9936-3124 1 , 2 , 3 , 4 ,
• Beatriz Herrera-Malaver   ORCID: orcid.org/0000-0002-5096-9974 1 , 2 , 3 ,
• Christophe Vanderaa   ORCID: orcid.org/0000-0001-7443-5427 4 ,
• Florian A. Theßeling 1 , 2 , 3 ,
• Łukasz Kreft   ORCID: orcid.org/0000-0001-7620-4657 5 ,
• Alexander Botzki   ORCID: orcid.org/0000-0001-6691-4233 5 ,
• Philippe Malcorps 6 ,
• Luk Daenen 6 ,
• Tom Wenseleers   ORCID: orcid.org/0000-0002-1434-861X 4 &
• Kevin J. Verstrepen   ORCID: orcid.org/0000-0002-3077-6219 1 , 2 , 3  

Nature Communications volume  15 , Article number:  2368 ( 2024 ) Cite this article

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• Chemical engineering
• Gas chromatography
• Machine learning
• Metabolomics
• Taste receptors

The perception and appreciation of food flavor depends on many interacting chemical compounds and external factors, and therefore proves challenging to understand and predict. Here, we combine extensive chemical and sensory analyses of 250 different beers to train machine learning models that allow predicting flavor and consumer appreciation. For each beer, we measure over 200 chemical properties, perform quantitative descriptive sensory analysis with a trained tasting panel and map data from over 180,000 consumer reviews to train 10 different machine learning models. The best-performing algorithm, Gradient Boosting, yields models that significantly outperform predictions based on conventional statistics and accurately predict complex food features and consumer appreciation from chemical profiles. Model dissection allows identifying specific and unexpected compounds as drivers of beer flavor and appreciation. Adding these compounds results in variants of commercial alcoholic and non-alcoholic beers with improved consumer appreciation. Together, our study reveals how big data and machine learning uncover complex links between food chemistry, flavor and consumer perception, and lays the foundation to develop novel, tailored foods with superior flavors.

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Introduction

Predicting and understanding food perception and appreciation is one of the major challenges in food science. Accurate modeling of food flavor and appreciation could yield important opportunities for both producers and consumers, including quality control, product fingerprinting, counterfeit detection, spoilage detection, and the development of new products and product combinations (food pairing) 1 , 2 , 3 , 4 , 5 , 6 . Accurate models for flavor and consumer appreciation would contribute greatly to our scientific understanding of how humans perceive and appreciate flavor. Moreover, accurate predictive models would also facilitate and standardize existing food assessment methods and could supplement or replace assessments by trained and consumer tasting panels, which are variable, expensive and time-consuming 7 , 8 , 9 . Lastly, apart from providing objective, quantitative, accurate and contextual information that can help producers, models can also guide consumers in understanding their personal preferences 10 .

Despite the myriad of applications, predicting food flavor and appreciation from its chemical properties remains a largely elusive goal in sensory science, especially for complex food and beverages 11 , 12 . A key obstacle is the immense number of flavor-active chemicals underlying food flavor. Flavor compounds can vary widely in chemical structure and concentration, making them technically challenging and labor-intensive to quantify, even in the face of innovations in metabolomics, such as non-targeted metabolic fingerprinting 13 , 14 . Moreover, sensory analysis is perhaps even more complicated. Flavor perception is highly complex, resulting from hundreds of different molecules interacting at the physiochemical and sensorial level. Sensory perception is often non-linear, characterized by complex and concentration-dependent synergistic and antagonistic effects 15 , 16 , 17 , 18 , 19 , 20 , 21 that are further convoluted by the genetics, environment, culture and psychology of consumers 22 , 23 , 24 . Perceived flavor is therefore difficult to measure, with problems of sensitivity, accuracy, and reproducibility that can only be resolved by gathering sufficiently large datasets 25 . Trained tasting panels are considered the prime source of quality sensory data, but require meticulous training, are low throughput and high cost. Public databases containing consumer reviews of food products could provide a valuable alternative, especially for studying appreciation scores, which do not require formal training 25 . Public databases offer the advantage of amassing large amounts of data, increasing the statistical power to identify potential drivers of appreciation. However, public datasets suffer from biases, including a bias in the volunteers that contribute to the database, as well as confounding factors such as price, cult status and psychological conformity towards previous ratings of the product.

Classical multivariate statistics and machine learning methods have been used to predict flavor of specific compounds by, for example, linking structural properties of a compound to its potential biological activities or linking concentrations of specific compounds to sensory profiles 1 , 26 . Importantly, most previous studies focused on predicting organoleptic properties of single compounds (often based on their chemical structure) 27 , 28 , 29 , 30 , 31 , 32 , 33 , thus ignoring the fact that these compounds are present in a complex matrix in food or beverages and excluding complex interactions between compounds. Moreover, the classical statistics commonly used in sensory science 34 , 35 , 36 , 37 , 38 , 39 require a large sample size and sufficient variance amongst predictors to create accurate models. They are not fit for studying an extensive set of hundreds of interacting flavor compounds, since they are sensitive to outliers, have a high tendency to overfit and are less suited for non-linear and discontinuous relationships 40 .

In this study, we combine extensive chemical analyses and sensory data of a set of different commercial beers with machine learning approaches to develop models that predict taste, smell, mouthfeel and appreciation from compound concentrations. Beer is particularly suited to model the relationship between chemistry, flavor and appreciation. First, beer is a complex product, consisting of thousands of flavor compounds that partake in complex sensory interactions 41 , 42 , 43 . This chemical diversity arises from the raw materials (malt, yeast, hops, water and spices) and biochemical conversions during the brewing process (kilning, mashing, boiling, fermentation, maturation and aging) 44 , 45 . Second, the advent of the internet saw beer consumers embrace online review platforms, such as RateBeer (ZX Ventures, Anheuser-Busch InBev SA/NV) and BeerAdvocate (Next Glass, inc.). In this way, the beer community provides massive data sets of beer flavor and appreciation scores, creating extraordinarily large sensory databases to complement the analyses of our professional sensory panel. Specifically, we characterize over 200 chemical properties of 250 commercial beers, spread across 22 beer styles, and link these to the descriptive sensory profiling data of a 16-person in-house trained tasting panel and data acquired from over 180,000 public consumer reviews. These unique and extensive datasets enable us to train a suite of machine learning models to predict flavor and appreciation from a beer’s chemical profile. Dissection of the best-performing models allows us to pinpoint specific compounds as potential drivers of beer flavor and appreciation. Follow-up experiments confirm the importance of these compounds and ultimately allow us to significantly improve the flavor and appreciation of selected commercial beers. Together, our study represents a significant step towards understanding complex flavors and reinforces the value of machine learning to develop and refine complex foods. In this way, it represents a stepping stone for further computer-aided food engineering applications 46 .

To generate a comprehensive dataset on beer flavor, we selected 250 commercial Belgian beers across 22 different beer styles (Supplementary Fig.  S1 ). Beers with ≤ 4.2% alcohol by volume (ABV) were classified as non-alcoholic and low-alcoholic. Blonds and Tripels constitute a significant portion of the dataset (12.4% and 11.2%, respectively) reflecting their presence on the Belgian beer market and the heterogeneity of beers within these styles. By contrast, lager beers are less diverse and dominated by a handful of brands. Rare styles such as Brut or Faro make up only a small fraction of the dataset (2% and 1%, respectively) because fewer of these beers are produced and because they are dominated by distinct characteristics in terms of flavor and chemical composition.

Extensive analysis identifies relationships between chemical compounds in beer

For each beer, we measured 226 different chemical properties, including common brewing parameters such as alcohol content, iso-alpha acids, pH, sugar concentration 47 , and over 200 flavor compounds (Methods, Supplementary Table  S1 ). A large portion (37.2%) are terpenoids arising from hopping, responsible for herbal and fruity flavors 16 , 48 . A second major category are yeast metabolites, such as esters and alcohols, that result in fruity and solvent notes 48 , 49 , 50 . Other measured compounds are primarily derived from malt, or other microbes such as non- Saccharomyces yeasts and bacteria (‘wild flora’). Compounds that arise from spices or staling are labeled under ‘Others’. Five attributes (caloric value, total acids and total ester, hop aroma and sulfur compounds) are calculated from multiple individually measured compounds.

As a first step in identifying relationships between chemical properties, we determined correlations between the concentrations of the compounds (Fig.  1 , upper panel, Supplementary Data  1 and 2 , and Supplementary Fig.  S2 . For the sake of clarity, only a subset of the measured compounds is shown in Fig.  1 ). Compounds of the same origin typically show a positive correlation, while absence of correlation hints at parameters varying independently. For example, the hop aroma compounds citronellol, and alpha-terpineol show moderate correlations with each other (Spearman’s rho=0.39 and 0.57), but not with the bittering hop component iso-alpha acids (Spearman’s rho=0.16 and −0.07). This illustrates how brewers can independently modify hop aroma and bitterness by selecting hop varieties and dosage time. If hops are added early in the boiling phase, chemical conversions increase bitterness while aromas evaporate, conversely, late addition of hops preserves aroma but limits bitterness 51 . Similarly, hop-derived iso-alpha acids show a strong anti-correlation with lactic acid and acetic acid, likely reflecting growth inhibition of lactic acid and acetic acid bacteria, or the consequent use of fewer hops in sour beer styles, such as West Flanders ales and Fruit beers, that rely on these bacteria for their distinct flavors 52 . Finally, yeast-derived esters (ethyl acetate, ethyl decanoate, ethyl hexanoate, ethyl octanoate) and alcohols (ethanol, isoamyl alcohol, isobutanol, and glycerol), correlate with Spearman coefficients above 0.5, suggesting that these secondary metabolites are correlated with the yeast genetic background and/or fermentation parameters and may be difficult to influence individually, although the choice of yeast strain may offer some control 53 .

Spearman rank correlations are shown. Descriptors are grouped according to their origin (malt (blue), hops (green), yeast (red), wild flora (yellow), Others (black)), and sensory aspect (aroma, taste, palate, and overall appreciation). Please note that for the chemical compounds, for the sake of clarity, only a subset of the total number of measured compounds is shown, with an emphasis on the key compounds for each source. For more details, see the main text and Methods section. Chemical data can be found in Supplementary Data  1 , correlations between all chemical compounds are depicted in Supplementary Fig.  S2 and correlation values can be found in Supplementary Data  2 . See Supplementary Data  4 for sensory panel assessments and Supplementary Data  5 for correlation values between all sensory descriptors.

Interestingly, different beer styles show distinct patterns for some flavor compounds (Supplementary Fig.  S3 ). These observations agree with expectations for key beer styles, and serve as a control for our measurements. For instance, Stouts generally show high values for color (darker), while hoppy beers contain elevated levels of iso-alpha acids, compounds associated with bitter hop taste. Acetic and lactic acid are not prevalent in most beers, with notable exceptions such as Kriek, Lambic, Faro, West Flanders ales and Flanders Old Brown, which use acid-producing bacteria ( Lactobacillus and Pediococcus ) or unconventional yeast ( Brettanomyces ) 54 , 55 . Glycerol, ethanol and esters show similar distributions across all beer styles, reflecting their common origin as products of yeast metabolism during fermentation 45 , 53 . Finally, low/no-alcohol beers contain low concentrations of glycerol and esters. This is in line with the production process for most of the low/no-alcohol beers in our dataset, which are produced through limiting fermentation or by stripping away alcohol via evaporation or dialysis, with both methods having the unintended side-effect of reducing the amount of flavor compounds in the final beer 56 , 57 .

Besides expected associations, our data also reveals less trivial associations between beer styles and specific parameters. For example, geraniol and citronellol, two monoterpenoids responsible for citrus, floral and rose flavors and characteristic of Citra hops, are found in relatively high amounts in Christmas, Saison, and Brett/co-fermented beers, where they may originate from terpenoid-rich spices such as coriander seeds instead of hops 58 .

Tasting panel assessments reveal sensorial relationships in beer

To assess the sensory profile of each beer, a trained tasting panel evaluated each of the 250 beers for 50 sensory attributes, including different hop, malt and yeast flavors, off-flavors and spices. Panelists used a tasting sheet (Supplementary Data  3 ) to score the different attributes. Panel consistency was evaluated by repeating 12 samples across different sessions and performing ANOVA. In 95% of cases no significant difference was found across sessions ( p  > 0.05), indicating good panel consistency (Supplementary Table  S2 ).

Aroma and taste perception reported by the trained panel are often linked (Fig.  1 , bottom left panel and Supplementary Data  4 and 5 ), with high correlations between hops aroma and taste (Spearman’s rho=0.83). Bitter taste was found to correlate with hop aroma and taste in general (Spearman’s rho=0.80 and 0.69), and particularly with “grassy” noble hops (Spearman’s rho=0.75). Barnyard flavor, most often associated with sour beers, is identified together with stale hops (Spearman’s rho=0.97) that are used in these beers. Lactic and acetic acid, which often co-occur, are correlated (Spearman’s rho=0.66). Interestingly, sweetness and bitterness are anti-correlated (Spearman’s rho = −0.48), confirming the hypothesis that they mask each other 59 , 60 . Beer body is highly correlated with alcohol (Spearman’s rho = 0.79), and overall appreciation is found to correlate with multiple aspects that describe beer mouthfeel (alcohol, carbonation; Spearman’s rho= 0.32, 0.39), as well as with hop and ester aroma intensity (Spearman’s rho=0.39 and 0.35).

Similar to the chemical analyses, sensorial analyses confirmed typical features of specific beer styles (Supplementary Fig.  S4 ). For example, sour beers (Faro, Flanders Old Brown, Fruit beer, Kriek, Lambic, West Flanders ale) were rated acidic, with flavors of both acetic and lactic acid. Hoppy beers were found to be bitter and showed hop-associated aromas like citrus and tropical fruit. Malt taste is most detected among scotch, stout/porters, and strong ales, while low/no-alcohol beers, which often have a reputation for being ‘worty’ (reminiscent of unfermented, sweet malt extract) appear in the middle. Unsurprisingly, hop aromas are most strongly detected among hoppy beers. Like its chemical counterpart (Supplementary Fig.  S3 ), acidity shows a right-skewed distribution, with the most acidic beers being Krieks, Lambics, and West Flanders ales.

Tasting panel assessments of specific flavors correlate with chemical composition

We find that the concentrations of several chemical compounds strongly correlate with specific aroma or taste, as evaluated by the tasting panel (Fig.  2 , Supplementary Fig.  S5 , Supplementary Data  6 ). In some cases, these correlations confirm expectations and serve as a useful control for data quality. For example, iso-alpha acids, the bittering compounds in hops, strongly correlate with bitterness (Spearman’s rho=0.68), while ethanol and glycerol correlate with tasters’ perceptions of alcohol and body, the mouthfeel sensation of fullness (Spearman’s rho=0.82/0.62 and 0.72/0.57 respectively) and darker color from roasted malts is a good indication of malt perception (Spearman’s rho=0.54).

Heatmap colors indicate Spearman’s Rho. Axes are organized according to sensory categories (aroma, taste, mouthfeel, overall), chemical categories and chemical sources in beer (malt (blue), hops (green), yeast (red), wild flora (yellow), Others (black)). See Supplementary Data  6 for all correlation values.

Interestingly, for some relationships between chemical compounds and perceived flavor, correlations are weaker than expected. For example, the rose-smelling phenethyl acetate only weakly correlates with floral aroma. This hints at more complex relationships and interactions between compounds and suggests a need for a more complex model than simple correlations. Lastly, we uncovered unexpected correlations. For instance, the esters ethyl decanoate and ethyl octanoate appear to correlate slightly with hop perception and bitterness, possibly due to their fruity flavor. Iron is anti-correlated with hop aromas and bitterness, most likely because it is also anti-correlated with iso-alpha acids. This could be a sign of metal chelation of hop acids 61 , given that our analyses measure unbound hop acids and total iron content, or could result from the higher iron content in dark and Fruit beers, which typically have less hoppy and bitter flavors 62 .

Public consumer reviews complement expert panel data

To complement and expand the sensory data of our trained tasting panel, we collected 180,000 reviews of our 250 beers from the online consumer review platform RateBeer. This provided numerical scores for beer appearance, aroma, taste, palate, overall quality as well as the average overall score.

Public datasets are known to suffer from biases, such as price, cult status and psychological conformity towards previous ratings of a product. For example, prices correlate with appreciation scores for these online consumer reviews (rho=0.49, Supplementary Fig.  S6 ), but not for our trained tasting panel (rho=0.19). This suggests that prices affect consumer appreciation, which has been reported in wine 63 , while blind tastings are unaffected. Moreover, we observe that some beer styles, like lagers and non-alcoholic beers, generally receive lower scores, reflecting that online reviewers are mostly beer aficionados with a preference for specialty beers over lager beers. In general, we find a modest correlation between our trained panel’s overall appreciation score and the online consumer appreciation scores (Fig.  3 , rho=0.29). Apart from the aforementioned biases in the online datasets, serving temperature, sample freshness and surroundings, which are all tightly controlled during the tasting panel sessions, can vary tremendously across online consumers and can further contribute to (among others, appreciation) differences between the two categories of tasters. Importantly, in contrast to the overall appreciation scores, for many sensory aspects the results from the professional panel correlated well with results obtained from RateBeer reviews. Correlations were highest for features that are relatively easy to recognize even for untrained tasters, like bitterness, sweetness, alcohol and malt aroma (Fig.  3 and below).

RateBeer text mining results can be found in Supplementary Data  7 . Rho values shown are Spearman correlation values, with asterisks indicating significant correlations ( p  < 0.05, two-sided). All p values were smaller than 0.001, except for Esters aroma (0.0553), Esters taste (0.3275), Esters aroma—banana (0.0019), Coriander (0.0508) and Diacetyl (0.0134).

Besides collecting consumer appreciation from these online reviews, we developed automated text analysis tools to gather additional data from review texts (Supplementary Data  7 ). Processing review texts on the RateBeer database yielded comparable results to the scores given by the trained panel for many common sensory aspects, including acidity, bitterness, sweetness, alcohol, malt, and hop tastes (Fig.  3 ). This is in line with what would be expected, since these attributes require less training for accurate assessment and are less influenced by environmental factors such as temperature, serving glass and odors in the environment. Consumer reviews also correlate well with our trained panel for 4-vinyl guaiacol, a compound associated with a very characteristic aroma. By contrast, correlations for more specific aromas like ester, coriander or diacetyl are underrepresented in the online reviews, underscoring the importance of using a trained tasting panel and standardized tasting sheets with explicit factors to be scored for evaluating specific aspects of a beer. Taken together, our results suggest that public reviews are trustworthy for some, but not all, flavor features and can complement or substitute taste panel data for these sensory aspects.

Models can predict beer sensory profiles from chemical data

The rich datasets of chemical analyses, tasting panel assessments and public reviews gathered in the first part of this study provided us with a unique opportunity to develop predictive models that link chemical data to sensorial features. Given the complexity of beer flavor, basic statistical tools such as correlations or linear regression may not always be the most suitable for making accurate predictions. Instead, we applied different machine learning models that can model both simple linear and complex interactive relationships. Specifically, we constructed a set of regression models to predict (a) trained panel scores for beer flavor and quality and (b) public reviews’ appreciation scores from beer chemical profiles. We trained and tested 10 different models (Methods), 3 linear regression-based models (simple linear regression with first-order interactions (LR), lasso regression with first-order interactions (Lasso), partial least squares regressor (PLSR)), 5 decision tree models (AdaBoost regressor (ABR), extra trees (ET), gradient boosting regressor (GBR), random forest (RF) and XGBoost regressor (XGBR)), 1 support vector regression (SVR), and 1 artificial neural network (ANN) model.

To compare the performance of our machine learning models, the dataset was randomly split into a training and test set, stratified by beer style. After a model was trained on data in the training set, its performance was evaluated on its ability to predict the test dataset obtained from multi-output models (based on the coefficient of determination, see Methods). Additionally, individual-attribute models were ranked per descriptor and the average rank was calculated, as proposed by Korneva et al. 64 . Importantly, both ways of evaluating the models’ performance agreed in general. Performance of the different models varied (Table  1 ). It should be noted that all models perform better at predicting RateBeer results than results from our trained tasting panel. One reason could be that sensory data is inherently variable, and this variability is averaged out with the large number of public reviews from RateBeer. Additionally, all tree-based models perform better at predicting taste than aroma. Linear models (LR) performed particularly poorly, with negative R 2 values, due to severe overfitting (training set R 2  = 1). Overfitting is a common issue in linear models with many parameters and limited samples, especially with interaction terms further amplifying the number of parameters. L1 regularization (Lasso) successfully overcomes this overfitting, out-competing multiple tree-based models on the RateBeer dataset. Similarly, the dimensionality reduction of PLSR avoids overfitting and improves performance, to some extent. Still, tree-based models (ABR, ET, GBR, RF and XGBR) show the best performance, out-competing the linear models (LR, Lasso, PLSR) commonly used in sensory science 65 .

GBR models showed the best overall performance in predicting sensory responses from chemical information, with R 2 values up to 0.75 depending on the predicted sensory feature (Supplementary Table  S4 ). The GBR models predict consumer appreciation (RateBeer) better than our trained panel’s appreciation (R 2 value of 0.67 compared to R 2 value of 0.09) (Supplementary Table  S3 and Supplementary Table  S4 ). ANN models showed intermediate performance, likely because neural networks typically perform best with larger datasets 66 . The SVR shows intermediate performance, mostly due to the weak predictions of specific attributes that lower the overall performance (Supplementary Table  S4 ).

Model dissection identifies specific, unexpected compounds as drivers of consumer appreciation

Next, we leveraged our models to infer important contributors to sensory perception and consumer appreciation. Consumer preference is a crucial sensory aspects, because a product that shows low consumer appreciation scores often does not succeed commercially 25 . Additionally, the requirement for a large number of representative evaluators makes consumer trials one of the more costly and time-consuming aspects of product development. Hence, a model for predicting chemical drivers of overall appreciation would be a welcome addition to the available toolbox for food development and optimization.

Since GBR models on our RateBeer dataset showed the best overall performance, we focused on these models. Specifically, we used two approaches to identify important contributors. First, rankings of the most important predictors for each sensorial trait in the GBR models were obtained based on impurity-based feature importance (mean decrease in impurity). High-ranked parameters were hypothesized to be either the true causal chemical properties underlying the trait, to correlate with the actual causal properties, or to take part in sensory interactions affecting the trait 67 (Fig.  4A ). In a second approach, we used SHAP 68 to determine which parameters contributed most to the model for making predictions of consumer appreciation (Fig.  4B ). SHAP calculates parameter contributions to model predictions on a per-sample basis, which can be aggregated into an importance score.

A The impurity-based feature importance (mean deviance in impurity, MDI) calculated from the Gradient Boosting Regression (GBR) model predicting RateBeer appreciation scores. The top 15 highest ranked chemical properties are shown. B SHAP summary plot for the top 15 parameters contributing to our GBR model. Each point on the graph represents a sample from our dataset. The color represents the concentration of that parameter, with bluer colors representing low values and redder colors representing higher values. Greater absolute values on the horizontal axis indicate a higher impact of the parameter on the prediction of the model. C Spearman correlations between the 15 most important chemical properties and consumer overall appreciation. Numbers indicate the Spearman Rho correlation coefficient, and the rank of this correlation compared to all other correlations. The top 15 important compounds were determined using SHAP (panel B).

Both approaches identified ethyl acetate as the most predictive parameter for beer appreciation (Fig.  4 ). Ethyl acetate is the most abundant ester in beer with a typical ‘fruity’, ‘solvent’ and ‘alcoholic’ flavor, but is often considered less important than other esters like isoamyl acetate. The second most important parameter identified by SHAP is ethanol, the most abundant beer compound after water. Apart from directly contributing to beer flavor and mouthfeel, ethanol drastically influences the physical properties of beer, dictating how easily volatile compounds escape the beer matrix to contribute to beer aroma 69 . Importantly, it should also be noted that the importance of ethanol for appreciation is likely inflated by the very low appreciation scores of non-alcoholic beers (Supplementary Fig.  S4 ). Despite not often being considered a driver of beer appreciation, protein level also ranks highly in both approaches, possibly due to its effect on mouthfeel and body 70 . Lactic acid, which contributes to the tart taste of sour beers, is the fourth most important parameter identified by SHAP, possibly due to the generally high appreciation of sour beers in our dataset.

Interestingly, some of the most important predictive parameters for our model are not well-established as beer flavors or are even commonly regarded as being negative for beer quality. For example, our models identify methanethiol and ethyl phenyl acetate, an ester commonly linked to beer staling 71 , as a key factor contributing to beer appreciation. Although there is no doubt that high concentrations of these compounds are considered unpleasant, the positive effects of modest concentrations are not yet known 72 , 73 .

To compare our approach to conventional statistics, we evaluated how well the 15 most important SHAP-derived parameters correlate with consumer appreciation (Fig.  4C ). Interestingly, only 6 of the properties derived by SHAP rank amongst the top 15 most correlated parameters. For some chemical compounds, the correlations are so low that they would have likely been considered unimportant. For example, lactic acid, the fourth most important parameter, shows a bimodal distribution for appreciation, with sour beers forming a separate cluster, that is missed entirely by the Spearman correlation. Additionally, the correlation plots reveal outliers, emphasizing the need for robust analysis tools. Together, this highlights the need for alternative models, like the Gradient Boosting model, that better grasp the complexity of (beer) flavor.

Finally, to observe the relationships between these chemical properties and their predicted targets, partial dependence plots were constructed for the six most important predictors of consumer appreciation 74 , 75 , 76 (Supplementary Fig.  S7 ). One-way partial dependence plots show how a change in concentration affects the predicted appreciation. These plots reveal an important limitation of our models: appreciation predictions remain constant at ever-increasing concentrations. This implies that once a threshold concentration is reached, further increasing the concentration does not affect appreciation. This is false, as it is well-documented that certain compounds become unpleasant at high concentrations, including ethyl acetate (‘nail polish’) 77 and methanethiol (‘sulfury’ and ‘rotten cabbage’) 78 . The inability of our models to grasp that flavor compounds have optimal levels, above which they become negative, is a consequence of working with commercial beer brands where (off-)flavors are rarely too high to negatively impact the product. The two-way partial dependence plots show how changing the concentration of two compounds influences predicted appreciation, visualizing their interactions (Supplementary Fig.  S7 ). In our case, the top 5 parameters are dominated by additive or synergistic interactions, with high concentrations for both compounds resulting in the highest predicted appreciation.

To assess the robustness of our best-performing models and model predictions, we performed 100 iterations of the GBR, RF and ET models. In general, all iterations of the models yielded similar performance (Supplementary Fig.  S8 ). Moreover, the main predictors (including the top predictors ethanol and ethyl acetate) remained virtually the same, especially for GBR and RF. For the iterations of the ET model, we did observe more variation in the top predictors, which is likely a consequence of the model’s inherent random architecture in combination with co-correlations between certain predictors. However, even in this case, several of the top predictors (ethanol and ethyl acetate) remain unchanged, although their rank in importance changes (Supplementary Fig.  S8 ).

Next, we investigated if a combination of RateBeer and trained panel data into one consolidated dataset would lead to stronger models, under the hypothesis that such a model would suffer less from bias in the datasets. A GBR model was trained to predict appreciation on the combined dataset. This model underperformed compared to the RateBeer model, both in the native case and when including a dataset identifier (R 2  = 0.67, 0.26 and 0.42 respectively). For the latter, the dataset identifier is the most important feature (Supplementary Fig.  S9 ), while most of the feature importance remains unchanged, with ethyl acetate and ethanol ranking highest, like in the original model trained only on RateBeer data. It seems that the large variation in the panel dataset introduces noise, weakening the models’ performances and reliability. In addition, it seems reasonable to assume that both datasets are fundamentally different, with the panel dataset obtained by blind tastings by a trained professional panel.

Lastly, we evaluated whether beer style identifiers would further enhance the model’s performance. A GBR model was trained with parameters that explicitly encoded the styles of the samples. This did not improve model performance (R2 = 0.66 with style information vs R2 = 0.67). The most important chemical features are consistent with the model trained without style information (eg. ethanol and ethyl acetate), and with the exception of the most preferred (strong ale) and least preferred (low/no-alcohol) styles, none of the styles were among the most important features (Supplementary Fig.  S9 , Supplementary Table  S5 and S6 ). This is likely due to a combination of style-specific chemical signatures, such as iso-alpha acids and lactic acid, that implicitly convey style information to the original models, as well as the low number of samples belonging to some styles, making it difficult for the model to learn style-specific patterns. Moreover, beer styles are not rigorously defined, with some styles overlapping in features and some beers being misattributed to a specific style, all of which leads to more noise in models that use style parameters.

Model validation

To test if our predictive models give insight into beer appreciation, we set up experiments aimed at improving existing commercial beers. We specifically selected overall appreciation as the trait to be examined because of its complexity and commercial relevance. Beer flavor comprises a complex bouquet rather than single aromas and tastes 53 . Hence, adding a single compound to the extent that a difference is noticeable may lead to an unbalanced, artificial flavor. Therefore, we evaluated the effect of combinations of compounds. Because Blond beers represent the most extensive style in our dataset, we selected a beer from this style as the starting material for these experiments (Beer 64 in Supplementary Data  1 ).

In the first set of experiments, we adjusted the concentrations of compounds that made up the most important predictors of overall appreciation (ethyl acetate, ethanol, lactic acid, ethyl phenyl acetate) together with correlated compounds (ethyl hexanoate, isoamyl acetate, glycerol), bringing them up to 95 th percentile ethanol-normalized concentrations (Methods) within the Blond group (‘Spiked’ concentration in Fig.  5A ). Compared to controls, the spiked beers were found to have significantly improved overall appreciation among trained panelists, with panelist noting increased intensity of ester flavors, sweetness, alcohol, and body fullness (Fig.  5B ). To disentangle the contribution of ethanol to these results, a second experiment was performed without the addition of ethanol. This resulted in a similar outcome, including increased perception of alcohol and overall appreciation.

Adding the top chemical compounds, identified as best predictors of appreciation by our model, into poorly appreciated beers results in increased appreciation from our trained panel. Results of sensory tests between base beers and those spiked with compounds identified as the best predictors by the model. A Blond and Non/Low-alcohol (0.0% ABV) base beers were brought up to 95th-percentile ethanol-normalized concentrations within each style. B For each sensory attribute, tasters indicated the more intense sample and selected the sample they preferred. The numbers above the bars correspond to the p values that indicate significant changes in perceived flavor (two-sided binomial test: alpha 0.05, n  = 20 or 13).

In a last experiment, we tested whether using the model’s predictions can boost the appreciation of a non-alcoholic beer (beer 223 in Supplementary Data  1 ). Again, the addition of a mixture of predicted compounds (omitting ethanol, in this case) resulted in a significant increase in appreciation, body, ester flavor and sweetness.

Predicting flavor and consumer appreciation from chemical composition is one of the ultimate goals of sensory science. A reliable, systematic and unbiased way to link chemical profiles to flavor and food appreciation would be a significant asset to the food and beverage industry. Such tools would substantially aid in quality control and recipe development, offer an efficient and cost-effective alternative to pilot studies and consumer trials and would ultimately allow food manufacturers to produce superior, tailor-made products that better meet the demands of specific consumer groups more efficiently.

A limited set of studies have previously tried, to varying degrees of success, to predict beer flavor and beer popularity based on (a limited set of) chemical compounds and flavors 79 , 80 . Current sensitive, high-throughput technologies allow measuring an unprecedented number of chemical compounds and properties in a large set of samples, yielding a dataset that can train models that help close the gaps between chemistry and flavor, even for a complex natural product like beer. To our knowledge, no previous research gathered data at this scale (250 samples, 226 chemical parameters, 50 sensory attributes and 5 consumer scores) to disentangle and validate the chemical aspects driving beer preference using various machine-learning techniques. We find that modern machine learning models outperform conventional statistical tools, such as correlations and linear models, and can successfully predict flavor appreciation from chemical composition. This could be attributed to the natural incorporation of interactions and non-linear or discontinuous effects in machine learning models, which are not easily grasped by the linear model architecture. While linear models and partial least squares regression represent the most widespread statistical approaches in sensory science, in part because they allow interpretation 65 , 81 , 82 , modern machine learning methods allow for building better predictive models while preserving the possibility to dissect and exploit the underlying patterns. Of the 10 different models we trained, tree-based models, such as our best performing GBR, showed the best overall performance in predicting sensory responses from chemical information, outcompeting artificial neural networks. This agrees with previous reports for models trained on tabular data 83 . Our results are in line with the findings of Colantonio et al. who also identified the gradient boosting architecture as performing best at predicting appreciation and flavor (of tomatoes and blueberries, in their specific study) 26 . Importantly, besides our larger experimental scale, we were able to directly confirm our models’ predictions in vivo.

Our study confirms that flavor compound concentration does not always correlate with perception, suggesting complex interactions that are often missed by more conventional statistics and simple models. Specifically, we find that tree-based algorithms may perform best in developing models that link complex food chemistry with aroma. Furthermore, we show that massive datasets of untrained consumer reviews provide a valuable source of data, that can complement or even replace trained tasting panels, especially for appreciation and basic flavors, such as sweetness and bitterness. This holds despite biases that are known to occur in such datasets, such as price or conformity bias. Moreover, GBR models predict taste better than aroma. This is likely because taste (e.g. bitterness) often directly relates to the corresponding chemical measurements (e.g., iso-alpha acids), whereas such a link is less clear for aromas, which often result from the interplay between multiple volatile compounds. We also find that our models are best at predicting acidity and alcohol, likely because there is a direct relation between the measured chemical compounds (acids and ethanol) and the corresponding perceived sensorial attribute (acidity and alcohol), and because even untrained consumers are generally able to recognize these flavors and aromas.

The predictions of our final models, trained on review data, hold even for blind tastings with small groups of trained tasters, as demonstrated by our ability to validate specific compounds as drivers of beer flavor and appreciation. Since adding a single compound to the extent of a noticeable difference may result in an unbalanced flavor profile, we specifically tested our identified key drivers as a combination of compounds. While this approach does not allow us to validate if a particular single compound would affect flavor and/or appreciation, our experiments do show that this combination of compounds increases consumer appreciation.

It is important to stress that, while it represents an important step forward, our approach still has several major limitations. A key weakness of the GBR model architecture is that amongst co-correlating variables, the largest main effect is consistently preferred for model building. As a result, co-correlating variables often have artificially low importance scores, both for impurity and SHAP-based methods, like we observed in the comparison to the more randomized Extra Trees models. This implies that chemicals identified as key drivers of a specific sensory feature by GBR might not be the true causative compounds, but rather co-correlate with the actual causative chemical. For example, the high importance of ethyl acetate could be (partially) attributed to the total ester content, ethanol or ethyl hexanoate (rho=0.77, rho=0.72 and rho=0.68), while ethyl phenylacetate could hide the importance of prenyl isobutyrate and ethyl benzoate (rho=0.77 and rho=0.76). Expanding our GBR model to include beer style as a parameter did not yield additional power or insight. This is likely due to style-specific chemical signatures, such as iso-alpha acids and lactic acid, that implicitly convey style information to the original model, as well as the smaller sample size per style, limiting the power to uncover style-specific patterns. This can be partly attributed to the curse of dimensionality, where the high number of parameters results in the models mainly incorporating single parameter effects, rather than complex interactions such as style-dependent effects 67 . A larger number of samples may overcome some of these limitations and offer more insight into style-specific effects. On the other hand, beer style is not a rigid scientific classification, and beers within one style often differ a lot, which further complicates the analysis of style as a model factor.

Our study is limited to beers from Belgian breweries. Although these beers cover a large portion of the beer styles available globally, some beer styles and consumer patterns may be missing, while other features might be overrepresented. For example, many Belgian ales exhibit yeast-driven flavor profiles, which is reflected in the chemical drivers of appreciation discovered by this study. In future work, expanding the scope to include diverse markets and beer styles could lead to the identification of even more drivers of appreciation and better models for special niche products that were not present in our beer set.

In addition to inherent limitations of GBR models, there are also some limitations associated with studying food aroma. Even if our chemical analyses measured most of the known aroma compounds, the total number of flavor compounds in complex foods like beer is still larger than the subset we were able to measure in this study. For example, hop-derived thiols, that influence flavor at very low concentrations, are notoriously difficult to measure in a high-throughput experiment. Moreover, consumer perception remains subjective and prone to biases that are difficult to avoid. It is also important to stress that the models are still immature and that more extensive datasets will be crucial for developing more complete models in the future. Besides more samples and parameters, our dataset does not include any demographic information about the tasters. Including such data could lead to better models that grasp external factors like age and culture. Another limitation is that our set of beers consists of high-quality end-products and lacks beers that are unfit for sale, which limits the current model in accurately predicting products that are appreciated very badly. Finally, while models could be readily applied in quality control, their use in sensory science and product development is restrained by their inability to discern causal relationships. Given that the models cannot distinguish compounds that genuinely drive consumer perception from those that merely correlate, validation experiments are essential to identify true causative compounds.

Despite the inherent limitations, dissection of our models enabled us to pinpoint specific molecules as potential drivers of beer aroma and consumer appreciation, including compounds that were unexpected and would not have been identified using standard approaches. Important drivers of beer appreciation uncovered by our models include protein levels, ethyl acetate, ethyl phenyl acetate and lactic acid. Currently, many brewers already use lactic acid to acidify their brewing water and ensure optimal pH for enzymatic activity during the mashing process. Our results suggest that adding lactic acid can also improve beer appreciation, although its individual effect remains to be tested. Interestingly, ethanol appears to be unnecessary to improve beer appreciation, both for blond beer and alcohol-free beer. Given the growing consumer interest in alcohol-free beer, with a predicted annual market growth of >7% 84 , it is relevant for brewers to know what compounds can further increase consumer appreciation of these beers. Hence, our model may readily provide avenues to further improve the flavor and consumer appreciation of both alcoholic and non-alcoholic beers, which is generally considered one of the key challenges for future beer production.

Whereas we see a direct implementation of our results for the development of superior alcohol-free beverages and other food products, our study can also serve as a stepping stone for the development of novel alcohol-containing beverages. We want to echo the growing body of scientific evidence for the negative effects of alcohol consumption, both on the individual level by the mutagenic, teratogenic and carcinogenic effects of ethanol 85 , 86 , as well as the burden on society caused by alcohol abuse and addiction. We encourage the use of our results for the production of healthier, tastier products, including novel and improved beverages with lower alcohol contents. Furthermore, we strongly discourage the use of these technologies to improve the appreciation or addictive properties of harmful substances.

The present work demonstrates that despite some important remaining hurdles, combining the latest developments in chemical analyses, sensory analysis and modern machine learning methods offers exciting avenues for food chemistry and engineering. Soon, these tools may provide solutions in quality control and recipe development, as well as new approaches to sensory science and flavor research.

Beer selection

250 commercial Belgian beers were selected to cover the broad diversity of beer styles and corresponding diversity in chemical composition and aroma. See Supplementary Fig.  S1 .

Chemical dataset

Sample preparation.

Beers within their expiration date were purchased from commercial retailers. Samples were prepared in biological duplicates at room temperature, unless explicitly stated otherwise. Bottle pressure was measured with a manual pressure device (Steinfurth Mess-Systeme GmbH) and used to calculate CO 2 concentration. The beer was poured through two filter papers (Macherey-Nagel, 500713032 MN 713 ¼) to remove carbon dioxide and prevent spontaneous foaming. Samples were then prepared for measurements by targeted Headspace-Gas Chromatography-Flame Ionization Detector/Flame Photometric Detector (HS-GC-FID/FPD), Headspace-Solid Phase Microextraction-Gas Chromatography-Mass Spectrometry (HS-SPME-GC-MS), colorimetric analysis, enzymatic analysis, Near-Infrared (NIR) analysis, as described in the sections below. The mean values of biological duplicates are reported for each compound.

HS-GC-FID/FPD

HS-GC-FID/FPD (Shimadzu GC 2010 Plus) was used to measure higher alcohols, acetaldehyde, esters, 4-vinyl guaicol, and sulfur compounds. Each measurement comprised 5 ml of sample pipetted into a 20 ml glass vial containing 1.75 g NaCl (VWR, 27810.295). 100 µl of 2-heptanol (Sigma-Aldrich, H3003) (internal standard) solution in ethanol (Fisher Chemical, E/0650DF/C17) was added for a final concentration of 2.44 mg/L. Samples were flushed with nitrogen for 10 s, sealed with a silicone septum, stored at −80 °C and analyzed in batches of 20.

The GC was equipped with a DB-WAXetr column (length, 30 m; internal diameter, 0.32 mm; layer thickness, 0.50 µm; Agilent Technologies, Santa Clara, CA, USA) to the FID and an HP-5 column (length, 30 m; internal diameter, 0.25 mm; layer thickness, 0.25 µm; Agilent Technologies, Santa Clara, CA, USA) to the FPD. N 2 was used as the carrier gas. Samples were incubated for 20 min at 70 °C in the headspace autosampler (Flow rate, 35 cm/s; Injection volume, 1000 µL; Injection mode, split; Combi PAL autosampler, CTC analytics, Switzerland). The injector, FID and FPD temperatures were kept at 250 °C. The GC oven temperature was first held at 50 °C for 5 min and then allowed to rise to 80 °C at a rate of 5 °C/min, followed by a second ramp of 4 °C/min until 200 °C kept for 3 min and a final ramp of (4 °C/min) until 230 °C for 1 min. Results were analyzed with the GCSolution software version 2.4 (Shimadzu, Kyoto, Japan). The GC was calibrated with a 5% EtOH solution (VWR International) containing the volatiles under study (Supplementary Table  S7 ).

HS-SPME-GC-MS

HS-SPME-GC-MS (Shimadzu GCMS-QP-2010 Ultra) was used to measure additional volatile compounds, mainly comprising terpenoids and esters. Samples were analyzed by HS-SPME using a triphase DVB/Carboxen/PDMS 50/30 μm SPME fiber (Supelco Co., Bellefonte, PA, USA) followed by gas chromatography (Thermo Fisher Scientific Trace 1300 series, USA) coupled to a mass spectrometer (Thermo Fisher Scientific ISQ series MS) equipped with a TriPlus RSH autosampler. 5 ml of degassed beer sample was placed in 20 ml vials containing 1.75 g NaCl (VWR, 27810.295). 5 µl internal standard mix was added, containing 2-heptanol (1 g/L) (Sigma-Aldrich, H3003), 4-fluorobenzaldehyde (1 g/L) (Sigma-Aldrich, 128376), 2,3-hexanedione (1 g/L) (Sigma-Aldrich, 144169) and guaiacol (1 g/L) (Sigma-Aldrich, W253200) in ethanol (Fisher Chemical, E/0650DF/C17). Each sample was incubated at 60 °C in the autosampler oven with constant agitation. After 5 min equilibration, the SPME fiber was exposed to the sample headspace for 30 min. The compounds trapped on the fiber were thermally desorbed in the injection port of the chromatograph by heating the fiber for 15 min at 270 °C.

The GC-MS was equipped with a low polarity RXi-5Sil MS column (length, 20 m; internal diameter, 0.18 mm; layer thickness, 0.18 µm; Restek, Bellefonte, PA, USA). Injection was performed in splitless mode at 320 °C, a split flow of 9 ml/min, a purge flow of 5 ml/min and an open valve time of 3 min. To obtain a pulsed injection, a programmed gas flow was used whereby the helium gas flow was set at 2.7 mL/min for 0.1 min, followed by a decrease in flow of 20 ml/min to the normal 0.9 mL/min. The temperature was first held at 30 °C for 3 min and then allowed to rise to 80 °C at a rate of 7 °C/min, followed by a second ramp of 2 °C/min till 125 °C and a final ramp of 8 °C/min with a final temperature of 270 °C.

Mass acquisition range was 33 to 550 amu at a scan rate of 5 scans/s. Electron impact ionization energy was 70 eV. The interface and ion source were kept at 275 °C and 250 °C, respectively. A mix of linear n-alkanes (from C7 to C40, Supelco Co.) was injected into the GC-MS under identical conditions to serve as external retention index markers. Identification and quantification of the compounds were performed using an in-house developed R script as described in Goelen et al. and Reher et al. 87 , 88 (for package information, see Supplementary Table  S8 ). Briefly, chromatograms were analyzed using AMDIS (v2.71) 89 to separate overlapping peaks and obtain pure compound spectra. The NIST MS Search software (v2.0 g) in combination with the NIST2017, FFNSC3 and Adams4 libraries were used to manually identify the empirical spectra, taking into account the expected retention time. After background subtraction and correcting for retention time shifts between samples run on different days based on alkane ladders, compound elution profiles were extracted and integrated using a file with 284 target compounds of interest, which were either recovered in our identified AMDIS list of spectra or were known to occur in beer. Compound elution profiles were estimated for every peak in every chromatogram over a time-restricted window using weighted non-negative least square analysis after which peak areas were integrated 87 , 88 . Batch effect correction was performed by normalizing against the most stable internal standard compound, 4-fluorobenzaldehyde. Out of all 284 target compounds that were analyzed, 167 were visually judged to have reliable elution profiles and were used for final analysis.

Discrete photometric and enzymatic analysis

Discrete photometric and enzymatic analysis (Thermo Scientific TM Gallery TM Plus Beermaster Discrete Analyzer) was used to measure acetic acid, ammonia, beta-glucan, iso-alpha acids, color, sugars, glycerol, iron, pH, protein, and sulfite. 2 ml of sample volume was used for the analyses. Information regarding the reagents and standard solutions used for analyses and calibrations is included in Supplementary Table  S7 and Supplementary Table  S9 .

NIR analyses

NIR analysis (Anton Paar Alcolyzer Beer ME System) was used to measure ethanol. Measurements comprised 50 ml of sample, and a 10% EtOH solution was used for calibration.

Correlation calculations

Pairwise Spearman Rank correlations were calculated between all chemical properties.

Sensory dataset

Trained panel.

Our trained tasting panel consisted of volunteers who gave prior verbal informed consent. All compounds used for the validation experiment were of food-grade quality. The tasting sessions were approved by the Social and Societal Ethics Committee of the KU Leuven (G-2022-5677-R2(MAR)). All online reviewers agreed to the Terms and Conditions of the RateBeer website.

Sensory analysis was performed according to the American Society of Brewing Chemists (ASBC) Sensory Analysis Methods 90 . 30 volunteers were screened through a series of triangle tests. The sixteen most sensitive and consistent tasters were retained as taste panel members. The resulting panel was diverse in age [22–42, mean: 29], sex [56% male] and nationality [7 different countries]. The panel developed a consensus vocabulary to describe beer aroma, taste and mouthfeel. Panelists were trained to identify and score 50 different attributes, using a 7-point scale to rate attributes’ intensity. The scoring sheet is included as Supplementary Data  3 . Sensory assessments took place between 10–12 a.m. The beers were served in black-colored glasses. Per session, between 5 and 12 beers of the same style were tasted at 12 °C to 16 °C. Two reference beers were added to each set and indicated as ‘Reference 1 & 2’, allowing panel members to calibrate their ratings. Not all panelists were present at every tasting. Scores were scaled by standard deviation and mean-centered per taster. Values are represented as z-scores and clustered by Euclidean distance. Pairwise Spearman correlations were calculated between taste and aroma sensory attributes. Panel consistency was evaluated by repeating samples on different sessions and performing ANOVA to identify differences, using the ‘stats’ package (v4.2.2) in R (for package information, see Supplementary Table  S8 ).

Online reviews from a public database

The ‘scrapy’ package in Python (v3.6) (for package information, see Supplementary Table  S8 ). was used to collect 232,288 online reviews (mean=922, min=6, max=5343) from RateBeer, an online beer review database. Each review entry comprised 5 numerical scores (appearance, aroma, taste, palate and overall quality) and an optional review text. The total number of reviews per reviewer was collected separately. Numerical scores were scaled and centered per rater, and mean scores were calculated per beer.

For the review texts, the language was estimated using the packages ‘langdetect’ and ‘langid’ in Python. Reviews that were classified as English by both packages were kept. Reviewers with fewer than 100 entries overall were discarded. 181,025 reviews from >6000 reviewers from >40 countries remained. Text processing was done using the ‘nltk’ package in Python. Texts were corrected for slang and misspellings; proper nouns and rare words that are relevant to the beer context were specified and kept as-is (‘Chimay’,’Lambic’, etc.). A dictionary of semantically similar sensorial terms, for example ‘floral’ and ‘flower’, was created and collapsed together into one term. Words were stemmed and lemmatized to avoid identifying words such as ‘acid’ and ‘acidity’ as separate terms. Numbers and punctuation were removed.

Sentences from up to 50 randomly chosen reviews per beer were manually categorized according to the aspect of beer they describe (appearance, aroma, taste, palate, overall quality—not to be confused with the 5 numerical scores described above) or flagged as irrelevant if they contained no useful information. If a beer contained fewer than 50 reviews, all reviews were manually classified. This labeled data set was used to train a model that classified the rest of the sentences for all beers 91 . Sentences describing taste and aroma were extracted, and term frequency–inverse document frequency (TFIDF) was implemented to calculate enrichment scores for sensorial words per beer.

The sex of the tasting subject was not considered when building our sensory database. Instead, results from different panelists were averaged, both for our trained panel (56% male, 44% female) and the RateBeer reviews (70% male, 30% female for RateBeer as a whole).

Beer price collection and processing

Beer prices were collected from the following stores: Colruyt, Delhaize, Total Wine, BeerHawk, The Belgian Beer Shop, The Belgian Shop, and Beer of Belgium. Where applicable, prices were converted to Euros and normalized per liter. Spearman correlations were calculated between these prices and mean overall appreciation scores from RateBeer and the taste panel, respectively.

Pairwise Spearman Rank correlations were calculated between all sensory properties.

Machine learning models

Predictive modeling of sensory profiles from chemical data.

Regression models were constructed to predict (a) trained panel scores for beer flavors and quality from beer chemical profiles and (b) public reviews’ appreciation scores from beer chemical profiles. Z-scores were used to represent sensory attributes in both data sets. Chemical properties with log-normal distributions (Shapiro-Wilk test, p  <  0.05 ) were log-transformed. Missing chemical measurements (0.1% of all data) were replaced with mean values per attribute. Observations from 250 beers were randomly separated into a training set (70%, 175 beers) and a test set (30%, 75 beers), stratified per beer style. Chemical measurements (p = 231) were normalized based on the training set average and standard deviation. In total, three linear regression-based models: linear regression with first-order interaction terms (LR), lasso regression with first-order interaction terms (Lasso) and partial least squares regression (PLSR); five decision tree models, Adaboost regressor (ABR), Extra Trees (ET), Gradient Boosting regressor (GBR), Random Forest (RF) and XGBoost regressor (XGBR); one support vector machine model (SVR) and one artificial neural network model (ANN) were trained. The models were implemented using the ‘scikit-learn’ package (v1.2.2) and ‘xgboost’ package (v1.7.3) in Python (v3.9.16). Models were trained, and hyperparameters optimized, using five-fold cross-validated grid search with the coefficient of determination (R 2 ) as the evaluation metric. The ANN (scikit-learn’s MLPRegressor) was optimized using Bayesian Tree-Structured Parzen Estimator optimization with the ‘Optuna’ Python package (v3.2.0). Individual models were trained per attribute, and a multi-output model was trained on all attributes simultaneously.

Model dissection

GBR was found to outperform other methods, resulting in models with the highest average R 2 values in both trained panel and public review data sets. Impurity-based rankings of the most important predictors for each predicted sensorial trait were obtained using the ‘scikit-learn’ package. To observe the relationships between these chemical properties and their predicted targets, partial dependence plots (PDP) were constructed for the six most important predictors of consumer appreciation 74 , 75 .

The ‘SHAP’ package in Python (v0.41.0) was implemented to provide an alternative ranking of predictor importance and to visualize the predictors’ effects as a function of their concentration 68 .

Validation of causal chemical properties

To validate the effects of the most important model features on predicted sensory attributes, beers were spiked with the chemical compounds identified by the models and descriptive sensory analyses were carried out according to the American Society of Brewing Chemists (ASBC) protocol 90 .

Compound spiking was done 30 min before tasting. Compounds were spiked into fresh beer bottles, that were immediately resealed and inverted three times. Fresh bottles of beer were opened for the same duration, resealed, and inverted thrice, to serve as controls. Pairs of spiked samples and controls were served simultaneously, chilled and in dark glasses as outlined in the Trained panel section above. Tasters were instructed to select the glass with the higher flavor intensity for each attribute (directional difference test 92 ) and to select the glass they prefer.

The final concentration after spiking was equal to the within-style average, after normalizing by ethanol concentration. This was done to ensure balanced flavor profiles in the final spiked beer. The same methods were applied to improve a non-alcoholic beer. Compounds were the following: ethyl acetate (Merck KGaA, W241415), ethyl hexanoate (Merck KGaA, W243906), isoamyl acetate (Merck KGaA, W205508), phenethyl acetate (Merck KGaA, W285706), ethanol (96%, Colruyt), glycerol (Merck KGaA, W252506), lactic acid (Merck KGaA, 261106).

Significant differences in preference or perceived intensity were determined by performing the two-sided binomial test on each attribute.

Reporting summary

Further information on research design is available in the  Nature Portfolio Reporting Summary linked to this article.

Data availability

The data that support the findings of this work are available in the Supplementary Data files and have been deposited to Zenodo under accession code 10653704 93 . The RateBeer scores data are under restricted access, they are not publicly available as they are property of RateBeer (ZX Ventures, USA). Access can be obtained from the authors upon reasonable request and with permission of RateBeer (ZX Ventures, USA).  Source data are provided with this paper.

Code availability

The code for training the machine learning models, analyzing the models, and generating the figures has been deposited to Zenodo under accession code 10653704 93 .

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Acknowledgements

We thank all lab members for their discussions and thank all tasting panel members for their contributions. Special thanks go out to Dr. Karin Voordeckers for her tremendous help in proofreading and improving the manuscript. M.S. was supported by a Baillet-Latour fellowship, L.C. acknowledges financial support from KU Leuven (C16/17/006), F.A.T. was supported by a PhD fellowship from FWO (1S08821N). Research in the lab of K.J.V. is supported by KU Leuven, FWO, VIB, VLAIO and the Brewing Science Serves Health Fund. Research in the lab of T.W. is supported by FWO (G.0A51.15) and KU Leuven (C16/17/006).

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These authors contributed equally: Michiel Schreurs, Supinya Piampongsant, Miguel Roncoroni.

Authors and Affiliations

VIB—KU Leuven Center for Microbiology, Gaston Geenslaan 1, B-3001, Leuven, Belgium

Michiel Schreurs, Supinya Piampongsant, Miguel Roncoroni, Lloyd Cool, Beatriz Herrera-Malaver, Florian A. Theßeling & Kevin J. Verstrepen

CMPG Laboratory of Genetics and Genomics, KU Leuven, Gaston Geenslaan 1, B-3001, Leuven, Belgium

Leuven Institute for Beer Research (LIBR), Gaston Geenslaan 1, B-3001, Leuven, Belgium

Laboratory of Socioecology and Social Evolution, KU Leuven, Naamsestraat 59, B-3000, Leuven, Belgium

Lloyd Cool, Christophe Vanderaa & Tom Wenseleers

VIB Bioinformatics Core, VIB, Rijvisschestraat 120, B-9052, Ghent, Belgium

Łukasz Kreft & Alexander Botzki

AB InBev SA/NV, Brouwerijplein 1, B-3000, Leuven, Belgium

Philippe Malcorps & Luk Daenen

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Contributions

S.P., M.S. and K.J.V. conceived the experiments. S.P., M.S. and K.J.V. designed the experiments. S.P., M.S., M.R., B.H. and F.A.T. performed the experiments. S.P., M.S., L.C., C.V., L.K., A.B., P.M., L.D., T.W. and K.J.V. contributed analysis ideas. S.P., M.S., L.C., C.V., T.W. and K.J.V. analyzed the data. All authors contributed to writing the manuscript.

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Correspondence to Kevin J. Verstrepen .

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K.J.V. is affiliated with bar.on. The other authors declare no competing interests.

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Schreurs, M., Piampongsant, S., Roncoroni, M. et al. Predicting and improving complex beer flavor through machine learning. Nat Commun 15 , 2368 (2024). https://doi.org/10.1038/s41467-024-46346-0

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DOI : https://doi.org/10.1038/s41467-024-46346-0

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Journal of Materials Chemistry A

Conductive nanocomposite hydrogels for flexible wearable sensors †.

* Corresponding authors

a MOE Engineering Research Center of Forestry Biomass Materials and Bioenergy, Beijing Key Laboratory of Lignocellulosic Chemistry, Research Center of Biomass Clean Utilization, College of Materials Science and Technology, Beijing Forestry University, Beijing 100083, PR China E-mail: [email protected]

b State Silica-based Materials Laboratory of Anhui Province, Bengbu 233000, PR China

In recent years, flexible wearable electronics have been widely used in smart wearable devices, micro-robots, and sensors due to their seamless integration with the human body and long-term monitoring capabilities. Hydrogels with good biocompatibility, versatility, and tunable mechanical properties compared to elastomers are becoming increasingly prominent in flexible electronics. Among them, conductive nanocomposite hydrogels have been extensively studied for their combination of multiple materials, resulting in higher elasticity, superior mechanical properties, and better physical/chemical/biological/electrical properties. Herein, we review the recent research advances in conductive nanocomposite hydrogels for sensor applications. First, we discuss the characteristics, design strategies, and applications of conductive nanocomposite hydrogels with different conductive compositions, including those based on carbon-based nanomaterials, polymer nanofillers, metal nanofillers, and the emerging 2D materials MXenes. Second, the properties of conductive nanocomposite hydrogels are described in detail, such as their mechanical properties, adhesion properties, self-healing properties, and anti-freezing properties. Finally, the design of future nanocomposite conducting hydrogel sensors is presented with their perspectives and challenges.

• This article is part of the themed collection: Journal of Materials Chemistry A Recent Review Articles

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Conductive nanocomposite hydrogels for flexible wearable sensors

W. Guo and M. Ma, J. Mater. Chem. A , 2024, Advance Article , DOI: 10.1039/D3TA08069B

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