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EPIMUTESTR: a nearest neighbor machine learning approach to predict cancer driver genes from the evolutionary action of coding variants.

Nucleic acids research - 8 Jul 2022

Parvandeh Saeid, Donehower Lawrence A, Panagiotis Katsonis, Hsu Teng-Kuei, Asmussen Jennifer K, Lee Kwanghyuk, Lichtarge Olivier

Abstract excerpt

Discovering rare cancer driver genes is difficult because their mutational frequency is too low for statistical detection by computational methods. EPIMUTESTR is an integrative nearest-neighbor machine learning algorithm that identifies such marginal genes by modeling the fitness of their mutations with the phylogenetic Evolutionary Action (EA) score. Over cohorts of sequenced patients from The Cancer Genome...

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Identifiers

PMID: 35412634
DOI: 10.1093/nar/gkac215
PMCID: PMC9262594

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026. Manifest publication-graph-cohort-2026-09-08.1.

Source receipt: pubmed, retrieved 7 Sept 2026.

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