Ranking cancer drivers via betweenness-based outlier detection and random walks
Abstract 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...
Main Authors: | , , |
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Format: | Article |
Language: | English |
Published: |
BMC
2021-02-01
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Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12859-021-03989-w |