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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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| Pubblicato in: | BMC Bioinformatics |
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| Autori principali: | , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2021
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7877041/ https://ncbi.nlm.nih.gov/pubmed/33568049 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-021-03989-w |
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