Article

Ranking Cancer Drivers via Betweenness-based Outlier Detection and Random Walks

2020-03-05

Abstract excerpt

<h4>Background</h4> Recent cancer genomic studies have generated detailed molecular data on a large number of cancer patients. A key remaining problem in cancer genomics is the identification of driver genes. <h4>Results:</h4> We propose BetweenNet, a computational approach that integrates genomic data with a protein-protein interaction network to identify cancer driver genes. BetweenNet utilizes a measure based...

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Literature Corpus work: 12f9b325-c27f-5095-b532-a969c42297bc
DOI: 10.1101/2020.03.03.974295

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