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Article

Prediction of cancer driver genes and mutations: the potential of integrative computational frameworks.

Briefings in bioinformatics - 22 Jan 2024

Nourbakhsh Mona, Degn Kristine, Saksager Astrid, Tiberti Matteo, Papaleo Elena

Abstract excerpt

The vast amount of available sequencing data allows the scientific community to explore different genetic alterations that may drive cancer or favor cancer progression. Software developers have proposed a myriad of predictive tools, allowing researchers and clinicians to compare and prioritize driver genes and mutations and their relative pathogenicity. However, there is little consensus on the computational...

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Identifiers

PMID: 38261338
DOI: 10.1093/bib/bbad519
PMCID: PMC10805075

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-07.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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