Artificial Intelligence, Machine Learning, and Bioinformatics in Molecular Mechanisms of Human Health and Disease
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Informatics".
Deadline for manuscript submissions: 30 April 2026
Special Issue Editor
Interests: bioinformatics; data science; machine learning; artificial intelligence; cancer; clinical trials; drug discovery; biomarkers
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Artificial intelligence (AI), machine learning (ML), and bioinformatics are revolutionizing our understanding of molecular mechanisms underlying human health and disease. These computational approaches are enabling the integration and analysis of large-scale biological data, leading to new insights into disease etiology, diagnosis, and therapeutic strategies. This Special Issue, “Artificial Intelligence, Machine Learning, and Bioinformatics in Molecular Mechanisms of Human Health and Disease,” aims to highlight cutting-edge research that leverages AI/ML and bioinformatics to uncover the molecular basis of health and disease.
We welcome original research papers, short communications, and review articles that cover topics including, but not limited to, the following:
- Development and application of AI and machine learning algorithms in bioinformatics for disease prediction, diagnosis, and treatment;
- Integration of multi-omics data (genomics, transcriptomics, proteomics, and metabolomics) to elucidate molecular mechanisms in health and disease;
- Computational modelling of molecular networks and pathways relevant to human diseases;
- Novel bioinformatics tools and databases for analyzing large-scale biological datasets;
- Applications of AI and bioinformatics in personalized medicine and precision health;
- Case studies demonstrating the impact of AI and bioinformatics on understanding complex diseases;
- Study of molecular processes linked to healthy aging, resilience, and adaptation using AI/ML and bioinformatics;
- Discovery of protective genetic factors and health-promoting molecular signatures using population genomics and AI/ML.
We look forward to receiving your contributions and advancing the interdisciplinary field of AI/ML and bioinformatics in molecular sciences.
Dr. Santosh Anand
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. International Journal of Molecular Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. There is an Article Processing Charge (APC) for publication in this open access journal. For details about the APC please see here. Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- artificial intelligence
- machine learning
- bioinformatics
- molecular mechanisms
- human health
- human disease
- multi-omics data
- molecular pathways
- personalized medicine
- disease biomarkers
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