Ranking cancer drivers via betweenness-based outlier detection and random walks

Background: 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. Results: We propose BetweenNet, a computational approach that integrates genomic data with a protei...

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Bibliographic Details
Main Authors: Erten, C. (Author), Houdjedj, A. (Author), Kazan, H. (Author)
Format: Article
Language:English
Published: BioMed Central Ltd 2021
Subjects:
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