Advanced Studies in Machine Learning for Computational Biology
A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "E3: Mathematical Biology".
Deadline for manuscript submissions: 20 October 2025 | Viewed by 34
Special Issue Editors
Interests: computational biology; machine learning modeling; generative AI
Interests: deep learning; bioinformatics; drug discovery; image processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid growth of high-throughput technologies has generated vast biological datasets, positioning computational biology as a critical field in deciphering complex biological systems. However, challenges remain in analyzing multidimensional data, modeling dynamic interactions, and predicting functional outcomes. Machine learning (ML) has emerged as a transformative tool, enabling robust pattern recognition, predictive modeling, and data-driven discovery on different scales, from molecular interactions to organismal systems.
This Special Issue will showcase cutting-edge ML methodologies tailored to computational biology, bridging the gap between algorithmic innovation and biological applications. Topics of interest include deep learning for omics sequence analysis, interpretable ML for biomarker identification, and scalable algorithms for single-cell omics integration. Submissions may also address ethical considerations and reproducibility frameworks that are unique to ML-driven biological research.
By showcasing interdisciplinary contributions from academia and industry, this Special Issue will provide a platform to disseminate reproducible, scalable, and translatable ML strategies. We encourage submissions that demonstrate rigorous validation against experimental data or address unmet needs in clinical and biotechnological applications. The insights shared will accelerate innovation, foster collaboration, and outline future directions for ML in computational biology, ultimately advancing precision medicine, drug discovery, and foundational biological discoveries.
Dr. Syed Dansih Ali
Dr. Hilal Tayara
Guest Editors
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. Mathematics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). 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
- machine learning
- computational biology
- deep learning
- predictive modeling
- biomarker discovery
- drug discovery
- precision medicine
- graph neural networks
- sequence analysis
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