Advances in Multi-Omics in Cancer: Second Edition
A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Oncology".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 9
Special Issue Editor
Interests: mass spectrometry-based proteomics; cancer; snake venom; scorpion venom; envenomation; toxins
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Omics-based approaches have profoundly advanced cancer research by enabling systematic investigations of the molecular mechanisms that drive tumor initiation, progression, metastasis, and therapeutic response. Genomics, epigenomics, transcriptomics, proteomics, metabolomics, lipidomics, and related technologies each provide unique and complementary insights into cancer biology.
While the integration of multiple omics layers offers a powerful framework for a systems-level understanding of cancer, high-quality studies based on individual omics approaches continue to play a fundamental role in identifying molecular alterations, biomarkers, and therapeutic targets. Such studies often provide the essential biological foundation for subsequent integrative and translational research.
Recent advances in data analysis, bioinformatics, and artificial intelligence have further expanded the potential of both single-omics and multi-omics studies by enhancing our ability to interpret data, recognize complex patterns, and enable knowledge discovery across diverse experimental designs.
This Special Issue aims to highlight original research articles, comprehensive reviews, methodological developments, and new computational advances that cover any omics approach applied to cancer research, as well as studies that integrate multiple molecular layers. Contributions addressing fundamental biological mechanisms, technological developments, and translational applications are all welcome.
Dr. Leo Kei Iwai
Guest Editor
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Keywords
- cancer
- multi-omics
- genomics
- transcriptomics
- proteomics
- metabolomics
- lipidomics
- epigenomics
- artificial intelligence
- machine learning
- systems biology
- biomarkers
- precision oncology
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