Cancer bioinformatics is the interdisciplinary application of computational methods, statistics, and data science to the molecular study of cancer. It develops and applies algorithms to analyze high-dimensional data from genomics, transcriptomics, proteomics, and related platforms in order to understand how tumors a…
Cancer bioinformatics is the interdisciplinary application of computational methods, statistics, and data science to the molecular study of cancer. It develops and applies algorithms to analyze high-dimensional data from genomics, transcriptomics, proteomics, and related platforms in order to understand how tumors arise, progress, and respond to therapy. Typical tasks include detecting somatic mutations and copy-number changes, identifying differentially expressed genes and proteins, characterizing the proteomic response to targeted agents, and analyzing single-nucleotide polymorphisms and other variants linked to disease risk and pathogenesis. Researchers integrate these data with reference databases and pathway and network models to nominate driver alterations, candidate biomarkers, and therapeutic targets, and to stratify tumors into clinically meaningful molecular subtypes. Cancer bioinformatics also supports diagnostic and prognostic classifier development, drug-response prediction, and reproducible, ion-current-based or label-free proteomic quantification. Reliable results depend on rigorous quality control, appropriate statistical testing with correction for multiple comparisons, and validation across independent cohorts. By linking molecular measurements to biological mechanism and clinical context, the field contributes to precision oncology, in which prevention, diagnosis, and treatment decisions are informed by the specific molecular profile of a patient's tumor, and it remains central to translating large-scale cancer datasets into actionable knowledge.
5 peer-reviewed articles, ranked by relevance. Each links to its DOI.
The 5 articles above have been cited 38 times in the scholarly literature. Citation data via OpenAlex and Crossref, updated Jun 2026.
A sample of recent works citing this journal's research on Cancer Bioinformatics, linking to each citing work.