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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Detalles Bibliográficos
Autores principales: Erten, Cesim, Houdjedj, Aissa, Kazan, Hilal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877041/
https://www.ncbi.nlm.nih.gov/pubmed/33568049
http://dx.doi.org/10.1186/s12859-021-03989-w

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7877041/
https://www.ncbi.nlm.nih.gov/pubmed/33568049
http://dx.doi.org/10.1186/s12859-021-03989-w

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