(ISSN 2577-5790)
OBM Genetics is an international Open Access journal published quarterly online by LIDSEN Publishing Inc. It accepts papers addressing basic and medical aspects of genetics and epigenetics and also ethical, legal and social issues. Coverage includes clinical, developmental, diagnostic, evolutionary, genomic, mitochondrial, molecular, oncological, population and reproductive aspects. It publishes a variety of article types (Original Research, Review, Communication, Opinion, Comment, Conference Report, Technical Note, Book Review, etc.). There is no restriction on the length of the papers and we encourage scientists to publish their results in as much detail as possible.
Special Issue
Integrative Analysis of Genetic Signatures and Physicochemical Informatics for Robust Detection of Complex Diseases
Submission Deadline: December 31, 2026 (Open) Submit Now
Guest Editor
Saurav Mallik, PhD
1. Department of Pharmacology & Toxicology, University of Arizona, Tucson, AZ, United States
2. Department of Environmental Health, Harvard T H Chan School of Public Health, Boston, MA, United States
Research Interests: Machine learning; deep learning; differential expression; gene signature; epigenetics; gene regulatory networks; graph mining
Co-Editors
Mingqiang Wang, PhD
Biomedical Sciences, School of Medicine, Stanford University, CA, USA
Research Interests: Genetics; bioinformatics; stem cell; cardiovascular biology; regenerative medicine
Hafiz Muhammad Fraz, PhD
Department of Mathematics, COMSATS University Islamabad, Lahore, Pakistan
Research Interests: Drug design and discovery; topological descriptors; graph embedding; energy of a graph; data analysis
Ankita Saha, MCA, PhD (pursuing)
Dept. of Computer Science, Swami Vivekananda University, Kolkata, India
Research Interests: Biomarker; differential expression analysis; biostatistics; data structure
About This Topic
This special issue basically covers the cutting-edge bioinformatics, Physicochemical informatics, biostatistics, and advanced graph embedding techniques used in precision health and healthcare therapeutic areas. In depth, it focuses on differential expression technologies (for gene dysregulated gene discovery), cancer classification model, signature discovery, gene regulatory network mining and hub gene discovery, aging clock model, cognitive learning, digital healthcare, molecular graph mining and quantitative structure-property relationship discovery (graph-theoretic descriptors and cheminformatics features), potential drug discovery, molecular docking, etc. We invite comprehensive reviews and original research for any computational and/or wet lab validation studies for the aforementioned topics are welcome in this special issue.
Keywords
Gene signature discovery; drug discovery; epigenetics; molecular graph mining; aging clock model; physicochemical informatics; digital healthcare; cognitive learning
Manuscript Submission Information
Manuscripts should be submitted through the LIDSEN Submission System. Detailed information on manuscript preparation and submission is available in the Instructions for Authors. All submitted articles will be thoroughly refereed through a single-blind peer-review process and will be processed following the Editorial Process and Quality Control policy. Upon acceptance, the article will be immediately published in a regular issue of the journal and will be listed together on the special issue website, with a label that the article belongs to the Special Issue. LIDSEN distributes articles under the Creative Commons Attribution (CC BY 4.0) License in an open-access model. The authors own the copyright to the article, and the article can be free to access, distribute, and reuse provided that the original work is correctly cited.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). Research articles and review articles are highly invited. Authors are encouraged to send the tentative title and abstract of the planned paper to the Editorial Office (genetics@lidsen.com) for record. If you have any questions, please do not hesitate to contact the Editorial Office.
Welcome your submission!
- Journal Metrics
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2024 
CiteScore SJR SNIP 0.7 0.147 0.167 - Newsletter