Computational and Multi-Omics Bioinformatics in Cancer Biology and Therapy Response
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: 31 July 2026 | Viewed by 12
Special Issue Editor
Interests: bioinformatics; epigenetics; cancer biology; metabolic disorders; integration of data; single cell biology; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Computational and multi‑omics bioinformatics have rapidly advanced with the growth of high‑throughput technologies in cancer research. The accumulation of large‑scale genomic, transcriptomic, epigenomic, proteomic, metabolomic, and clinical datasets has created an urgent need for integrative approaches to understand cancer biology and therapy response. The purpose of this Special Issue is to provide a platform for cutting‑edge work on computational and multi‑omics methods in cancer and to promote their translation toward precision oncology.
This Special Issue will focus on the computational, statistical, and AI‑driven analysis of multi‑omics and related data to elucidate tumor biology, identify biomarkers, and model treatment outcomes.
Subtopics include, but are not limited to, the following: integrative multi‑omics analysis for biomarker and subtype discovery; machine learning and deep learning for multi‑omics integration and therapy response prediction; computational modeling of drug sensitivity and resistance; multi‑omics‑based prognosis and outcome prediction; single‑cell and spatial multi‑omics analysis of intratumoral heterogeneity and the tumor microenvironment; multi‑omics studies of tumor–immune interactions and immunotherapy response; network‑ and pathway‑based approaches for target discovery; and translational pipelines combining multi‑omics with imaging, clinical, or real‑world data to support precision oncology and treatment decision‑making.
Dr. Prasoon Agarwal
Guest Editor
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Keywords
- cancer bioinformatics
- multi‑omics integration
- precision oncology
- tumor heterogeneity
- tumor microenvironment
- therapy response
- machine learning
- deep learning
- AI‑driven analysis
- single‑cell multi‑omics
- spatial omics
- immunotherapy
- tumor–immune interactions
- network biology
- pathway analysis
- biomarker discovery
- clinical outcome prediction
- translational bioinformatics
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