Advances in Bioinformatics and Multi-Omics Applications in Cancer Research
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 March 2026 | Viewed by 23
Special Issue Editor
Interests: bioinformatics and multi-omics data analysis in cancer research; statistical and machine learning approaches with applications in biomedical data analysis; computational statistics and monte carlo methods with applications in biomedical research
Special Issue Information
Dear Colleagues,
Recent advances in high-throughput technologies have enabled the generation of large-scale multi-omics datasets, including genomics, transcriptomics, epigenomics, proteomics, and metabolomics. The application and integration of these complex data using bioinformatics and computational approaches have become essential for uncovering the molecular mechanisms driving cancer initiation, progression, and therapeutic response.
This Special Issue aims to highlight recent developments and applications of bioinformatics and multi-omics data analysis in cancer research. We welcome original research and comprehensive reviews that address innovative computational methods, integrative analysis pipelines, machine learning and AI-driven approaches, as well as novel insights into cancer biology derived from multi-omics data. Topics of interest include, but are not limited to, biomarker discovery, patient stratification, therapeutic target identification, tumor heterogeneity, single-cell and spatial multi-omics, and systems biology approaches.
By bringing together interdisciplinary contributions, this Special Issue seeks to advance our understanding of cancer mechanisms and support the development of precision oncology strategies.
Dr. Yang Shi
Guest Editor
Manuscript Submission Information
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Keywords
- bioinformatics
- genomics
- transcriptomics
- epigenomics
- proteomics
- metabolomics
- multi-omics
- cancer research
- machine learning
- biomarker discovery
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