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Article

Identification of candidate cancer drivers by integrative Epi-DNA and Gene Expression (iEDGE) data analysis.

Scientific reports - 15 Nov 2019

Li Amy, Chapuy Bjoern, Varelas Xaralabos, Sebastiani Paola, Monti Stefano

Abstract excerpt

The emergence of large-scale multi-omics data warrants method development for data integration. Genomic studies from cancer patients have identified epigenetic and genetic regulators - such as methylation marks, somatic mutations, and somatic copy number alterations (SCNAs), among others - as predictive features of cancer outcome. However, identification of "driver genes" associated with a given alteration...

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Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

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Identifiers

PMID: 31729402
DOI: 10.1038/s41598-019-52886-z
PMCID: PMC6858347

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PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 6 Sept 2026. Manifest publication-graph-cohort-2026-09-06.1.

Source receipt: pubmed, retrieved 6 Sept 2026.

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