DNA sequence classification for diabetes mellitus using NuSVC and XGBoost: A comparative

Said A. Salloum; Khaled Mohammad Alomari; Ayham Salloum

doi:10.1371/journal.pone.0328253

Peer Review History

Original SubmissionFebruary 18, 2025
Decision Letter - Syed Nisar Hussain Bukhari, Editor Dear Dr. Salloum, Please submit your revised manuscript by Jun 12 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Syed Nisar Hussain Bukhari Academic Editor PLOS ONE Journal Requirements: When submitting your revision, we need you to address these additional requirements. 1.Please ensure that your manuscript meets PLOS ONE's style requirements, including those for file naming. The PLOS ONE style templates can be found at https://journals.plos.org/plosone/s/file?id=wjVg/PLOSOne_formatting_sample_main_body.pdf and https://journals.plos.org/plosone/s/file?id=ba62/PLOSOne_formatting_sample_title_authors_affiliations.pdf 2. Please note that PLOS ONE has specific guidelines on code sharing for submissions in which author-generated code underpins the findings in the manuscript. In these cases, we expect all author-generated code to be made available without restrictions upon publication of the work. Please review our guidelines at https://journals.plos.org/plosone/s/materials-and-software-sharing#loc-sharing-code and ensure that your code is shared in a way that follows best practice and facilitates reproducibility and reuse. 3. When completing the data availability statement of the submission form, you indicated that you will make your data available on acceptance. We strongly recommend all authors decide on a data sharing plan before acceptance, as the process can be lengthy and hold up publication timelines. Please note that, though access restrictions are acceptable now, your entire data will need to be made freely accessible if your manuscript is accepted for publication. This policy applies to all data except where public deposition would breach compliance with the protocol approved by your research ethics board. If you are unable to adhere to our open data policy, please kindly revise your statement to explain your reasoning and we will seek the editor's input on an exemption. Please be assured that, once you have provided your new statement, the assessment of your exemption will not hold up the peer review process. [Note: HTML markup is below. Please do not edit.] Reviewers' comments: Reviewer's Responses to Questions Comments to the Author 1. Is the manuscript technically sound, and do the data support the conclusions? Reviewer #1: Partly Reviewer #2: Partly ******** 2. Has the statistical analysis been performed appropriately and rigorously? -->?> Reviewer #1: Yes Reviewer #2: No ****** 3. Have the authors made all data underlying the findings in their manuscript fully available??> The PLOS Data policy Reviewer #1: Yes Reviewer #2: Yes ****** 4. Is the manuscript presented in an intelligible fashion and written in standard English??> Reviewer #1: Yes Reviewer #2: No ****** Reviewer #1: The manuscript is well written and caters to an Important Research Area in the domain of gnetic basis of diseases. However, the manuscript provides very little coverage of literature, does not describe dataset in detail. The authors are advised to provide more literature support and more insight in to the dataset. Also the comparison of onlY two machine learning algorithms does not fully validate the effectiveness of learning from the DNA sequence data. The authors are advised to compare their models with other established models using similar type of data. The data cleaning process is incompletely covered and should describe the process in detail. The authors are advised to include a graphical view of the model architecture to make the manuscript more intuitive. Reviewer #2: Major concerns Unjustified use of SMOTE on a balanced dataset The dataset is initially balanced (1,296 sequences per class). Applying SMOTE here is unnecessary and may introduce artificial patterns. Please clarify the class distribution after train/validation split and justify the need for oversampling. Lack of robust model validation Results are presented for a single 80–20 split. No k-fold cross‐validation or external test set is used, raising concerns about overfitting—especially given the perfect AUC of 1.00 for XGBoost. Please include repeated cross‐validation (e.g., 5- or 10-fold) and report mean ± SD for each metric. Missing statistical significance testing Differences in accuracy (98% vs 87%) and AUC (1.00 vs 0.95) require statistical validation (e.g., DeLong’s test for ROC curves). Report p-values or confidence intervals to demonstrate that XGBoost’s superiority is not due to chance. Insufficient hyperparameter and feature‐engineering detail The choice of k-mer sizes (k = 3 and 6) and TF-IDF parameters is not justified. Details of grid search (parameter ranges, scoring metric) are omitted. Please provide a complete description of all hyperparameters and preprocessing settings in either the Methods or a Supplementary Table. Misuse of terminology References to “training over 10 epochs” for XGBoost and NuSVC are incorrect: these models do not train in epochs. Replace with precise descriptions (e.g., number of boosting rounds for XGBoost, number of support vectors or CV folds for NuSVC). Overly optimistic performance claims An AUC of 1.00 and very low log loss suggest possible data leakage or overfitting. Please audit your data pipeline for any inadvertent overlap between training and validation sets (e.g., identical k-mer distributions). Minor concerns Several typos and grammatical issues (e.g., “datase) andted,” inconsistent heading capitalization). A thorough language edit is needed. Figures (ROC curve, loss plots, confusion matrices) lack axis labels and clear legends—enhance readability. Discussion should temper claims about clinical readiness: emphasize that further validation on independent cohorts is required. ****** what does this mean? ). If published, this will include your full peer review and any attached files. If you choose “no”, your identity will remain anonymous but your review may still be made public. Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy Reviewer #1: Yes: Nisar iqbal wani Reviewer #2: No ******** [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0328253.r001
Revision 1
14 May 2025 Author Response Dear Editor, The authors are really very grateful to the Journal Editor efforts in essentially discussing the paper reviews with the reviewers and identifying the further significant points for enhancements. The authors would also like to sincerely thank the reviewers for their valuable remarks and careful feedback which helped them to significantly enhance this work and its presentation. Regardless of the final outcome, the authors sincerely thank the editor and reviewers for supporting them. The productive and valuable remarks enable them to update many parts of the paper as shown by the responses to each comment. Besides, all the updated parts in the manuscript were highlighted in yellow color in order to be easily tracked by the editor and reviewers. Thank you again for allowing a resubmission of our manuscript, with an opportunity to address the reviewers’ comments. We are uploading (a) our point-by-point response to the comments (below) (response to reviewers, under “Author’s Response Files”), (b) an updated manuscript with yellow highlighting indicating changes (as “Highlighted PDF”), and (c) a clean updated manuscript without highlights (“Main Manuscript”). Best regards, Salloum et al. Attachments Attachment Submitted filename: Response to reviewers.docx https://doi.org/10.1371/journal.pone.0328253.r002
Decision Letter - Syed Nisar Hussain Bukhari, Editor PLOS ONE Dear Dr. Salloum, Thank you for submitting your manuscript to PLOS ONE. After careful consideration, we feel that it has merit but does not fully meet PLOS ONE’s publication criteria as it currently stands. Therefore, we invite you to submit a revised version of the manuscript that addresses the points raised during the review process. Address the following points before anything can be decided 1 The Authors need to state the novelty of their work 2 Authors may use deep learning methods and compare their technique accordingly 3 Latest research of 2024 and 2025 needs to be highlighted 4 Results need discussion in depth 5 Mathematical modelling needs to be incorporated 6 Manuscript should have an elaborated discussion section 7 Compare your work with the existing work as well Please submit your revised manuscript by Jul 19 2025 11:59PM. If you will need more time than this to complete your revisions, please reply to this message or contact the journal office at plosone@plos.org . When you're ready to submit your revision, log on to https://www.editorialmanager.com/pone/ and select the 'Submissions Needing Revision' folder to locate your manuscript file. A rebuttal letter that responds to each point raised by the academic editor and reviewer(s). You should upload this letter as a separate file labeled 'Response to Reviewers'. A marked-up copy of your manuscript that highlights changes made to the original version. You should upload this as a separate file labeled 'Revised Manuscript with Track Changes'. An unmarked version of your revised paper without tracked changes. You should upload this as a separate file labeled 'Manuscript'. If you would like to make changes to your financial disclosure, please include your updated statement in your cover letter. Guidelines for resubmitting your figure files are available below the reviewer comments at the end of this letter. If applicable, we recommend that you deposit your laboratory protocols in protocols.io to enhance the reproducibility of your results. Protocols.io assigns your protocol its own identifier (DOI) so that it can be cited independently in the future. For instructions see: https://journals.plos.org/plosone/s/submission-guidelines#loc-laboratory-protocols . Additionally, PLOS ONE offers an option for publishing peer-reviewed Lab Protocol articles, which describe protocols hosted on protocols.io. Read more information on sharing protocols at https://plos.org/protocols?utm_medium=editorial-email&utm_source=authorletters&utm_campaign=protocols . We look forward to receiving your revised manuscript. Kind regards, Syed Nisar Hussain Bukhari Academic Editor PLOS ONE [Note: HTML markup is below. Please do not edit.] [NOTE: If reviewer comments were submitted as an attachment file, they will be attached to this email and accessible via the submission site. Please log into your account, locate the manuscript record, and check for the action link "View Attachments". If this link does not appear, there are no attachment files.] While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ . PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Registration is free. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email PLOS at figures@plos.org . Please note that Supporting Information files do not need this step. https://doi.org/10.1371/journal.pone.0328253.r003
Revision 2
5 Jun 2025 Author Response Dear PLOS ONE Editorial Team, Thank you for your detailed review and the opportunity to revise our manuscript. We appreciate the constructive feedback provided by the reviewers and editorial board. We have carefully addressed all the requested points in our revised submission, which we are now resubmitting for further evaluation. Below is our point-by-point response to the requested revisions: 1. Novelty of the Work We have clearly stated the novelty of our study at the end of the Introduction. Specifically, we highlight the integration of TF-IDF on k-mer DNA sequences with traditional classifiers (NuSVC, XGBoost), a pipeline not widely explored for diabetes prediction, offering a balance between performance and interpretability. 2. Inclusion of Deep Learning Methods Although our study focuses on classical models, we have acknowledged the potential of deep learning and added a discussion outlining how models like CNNs and transformers could extend our pipeline. A future direction is now clearly described. 3. Highlighting of 2024 and 2025 Research We have cited and discussed recent works published in 2024 and 2025, particularly those applying advanced deep learning and multi-omics approaches in genomics and diabetes prediction. These references have been integrated into the Related Work section. 4. In-Depth Discussion of Results The Results section now includes a standalone, expanded Discussion that interprets model behavior, evaluates performance across metrics, and links findings to clinical implications. 5. Incorporation of Mathematical Modeling We embedded a section explaining the mathematical formulations behind TF-IDF, SMOTE, NuSVC optimization, and XGBoost’s objective function. Key equations and references have been included to clarify the modeling techniques used. 6. Elaborated Discussion Section A dedicated and detailed Discussion section has been added before the Conclusion. It explains the implications of the findings, compares classifiers, discusses clinical relevance, and links to current literature. 7. Comparison with Existing Work We added a comparative table and narrative analysis in the Discussion that contrasts our method with recent state-of-the-art models, including transformer-based and CNN hybrid systems, highlighting accuracy, scalability, and clinical readiness. Please let us know if any further clarification is required. We look forward to your feedback and the continued evaluation of our manuscript. Sincerely, Dr. Said Salloum Attachments Attachment Submitted filename: Response_to_reviewers_auresp_2.docx https://doi.org/10.1371/journal.pone.0328253.r004
Decision Letter - Syed Nisar Hussain Bukhari, Editor DNA Sequence Classification for Diabetes Mellitus using NuSVC and XGBoost A Comparative PONE-D-25-08630R2 Dear Dr. Salloum, We’re pleased to inform you that your manuscript has been judged scientifically suitable for publication and will be formally accepted for publication once it meets all outstanding technical requirements. Within one week, you’ll receive an e-mail detailing the required amendments. When these have been addressed, you’ll receive a formal acceptance letter and your manuscript will be scheduled for publication. An invoice will be generated when your article is formally accepted. Please note, if your institution has a publishing partnership with PLOS and your article meets the relevant criteria, all or part of your publication costs will be covered. Please make sure your user information is up-to-date by logging into Editorial Manager at Editorial Manager® and clicking the ‘Update My Information' link at the top of the page. If you have any questions relating to publication charges, please contact our Author Billing department directly at authorbilling@plos.org. If your institution or institutions have a press office, please notify them about your upcoming paper to help maximize its impact. If they’ll be preparing press materials, please inform our press team as soon as possible -- no later than 48 hours after receiving the formal acceptance. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. Kind regards, Syed Nisar Hussain Bukhari Academic Editor PLOS ONE Additional Editor Comments (optional): Reviewers' comments: https://doi.org/10.1371/journal.pone.0328253.r005
Formally Accepted
Acceptance Letter - Syed Nisar Hussain Bukhari, Editor PONE-D-25-08630R2 PLOS ONE Dear Dr. Salloum, I'm pleased to inform you that your manuscript has been deemed suitable for publication in PLOS ONE. Congratulations! Your manuscript is now being handed over to our production team. At this stage, our production department will prepare your paper for publication. This includes ensuring the following: * All references, tables, and figures are properly cited * All relevant supporting information is included in the manuscript submission, * There are no issues that prevent the paper from being properly typeset You will receive further instructions from the production team, including instructions on how to review your proof when it is ready. Please keep in mind that we are working through a large volume of accepted articles, so please give us a few days to review your paper and let you know the next and final steps. Lastly, if your institution or institutions have a press office, please let them know about your upcoming paper now to help maximize its impact. If they'll be preparing press materials, please inform our press team within the next 48 hours. Your manuscript will remain under strict press embargo until 2 pm Eastern Time on the date of publication. For more information, please contact onepress@plos.org. If we can help with anything else, please email us at customercare@plos.org. Thank you for submitting your work to PLOS ONE and supporting open access. Kind regards, PLOS ONE Editorial Office Staff on behalf of Dr. Syed Nisar Hussain Bukhari Academic Editor PLOS ONE https://doi.org/10.1371/journal.pone.0328253.r006

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