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HyperModules: identifying clinically and phenotypically significant network modules with disease mutations for biomarker discovery

Summary: Correlating disease mutations with clinical and phenotypic information such as drug response or patient survival is an important goal of personalized cancer genomics and a first step in biomarker discovery. HyperModules is a network search algorithm that finds frequently mutated gene module...

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Detalles Bibliográficos
Autores principales: Leung, Alvin, Bader, Gary D., Reimand, Jüri
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4103591/
https://www.ncbi.nlm.nih.gov/pubmed/24713437
http://dx.doi.org/10.1093/bioinformatics/btu172
Descripción
Sumario:Summary: Correlating disease mutations with clinical and phenotypic information such as drug response or patient survival is an important goal of personalized cancer genomics and a first step in biomarker discovery. HyperModules is a network search algorithm that finds frequently mutated gene modules with significant clinical or phenotypic signatures from biomolecular interaction networks. Availability and implementation: HyperModules is available in Cytoscape App Store and as a command line tool at www.baderlab.org/Sofware/HyperModules. Contact: Juri.Reimand@utoronto.ca or Gary.Bader@utoronto.ca Supplementary information: Supplementary data are available at Bioinformatics online