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

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 si...

Full description

Saved in:
Bibliographic Details
Published in:Bioinformatics (Oxford, England) England), 2014-08, Vol.30 (15), p.2230-2232
Main Authors: Leung, Alvin, Bader, Gary D, Reimand, Jüri
Format: Article
Language:English
Subjects:
Algorithms
Applications Notes
Biomarkers, Tumor - genetics
Computer Graphics
Gene Regulatory Networks
Genomics
Humans
Internet
Mutation
Neoplasms - genetics
Neoplasms - metabolism
Phenotype
Protein Interaction Maps
Software
Systems Biology - methods
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
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. HyperModules is available in Cytoscape App Store and as a command line tool at www.baderlab.org/Sofware/HyperModules. Juri.Reimand@utoronto.ca or Gary.Bader@utoronto.ca Supplementary data are available at Bioinformatics online.
ISSN:1367-4803
1367-4811
DOI:10.1093/bioinformatics/btu172