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

Alvin Leung, Gary D. Bader, Jüri Reimand
2014 Computer applications in the biosciences : CABIOS  
HyperModules is a network search algorithm that finds frequently mutated gene modules with significant clinical or phenotypic signatures from biomolecular interaction networks.  ...  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  ...  ACKNOWLEDGEMENTS The authors thank Jason Montojo and Harold Rodriguez for Cytoscape help. Conflict of Interest: none declared.  ... 
doi:10.1093/bioinformatics/btu172 pmid:24713437 pmcid:PMC4103591 fatcat:howfy3q5x5blrnd6pmdmjefzyq

Biological Networks for Cancer Candidate Biomarkers Discovery

Wenying Yan, Wenjin Xue, Jiajia Chen, Guang Hu
2016 Cancer Informatics  
A variety of genomic alterations, such as point mutations, copy number variations, and gene rearrangements, contribute  ...  identify significant mutated gene modules as potential multivariate biomarkers for cancer.  ...  Based on gene mutation information, biomolecular interaction networks, and patient clinical information, Leung et al. 15 developed a Cytoscape plug-in called HyperModules to clinically and phenotypically  ... 
doi:10.4137/cin.s39458 pmid:27625573 pmcid:PMC5012434 fatcat:zuqt2qdd7bejvfsex5dipfmbgy

Frequent mutations in acetylation and ubiquitination sites suggest novel driver mechanisms of cancer

Soumil Narayan, Gary D. Bader, Jüri Reimand
2016 Genome Medicine  
Integrated mutation analysis of clinical information and protein interaction networks suggests that many PTM-specific mutations associate with decreased patient survival.  ...  Gene-focused analysis with the ActiveDriver method reveals significant co-occurrences of acetylation and ubiquitination PTMs and mutation hotspots in known oncoproteins (TP53, AKT1, IDH1) and highlights  ...  Acknowledgements We gratefully acknowledge the contributions from TCGA Research Network and its TCGA Pan-Cancer Analysis Working Group.  ... 
doi:10.1186/s13073-016-0311-2 pmid:27175787 pmcid:PMC4864925 fatcat:lihgz2o7k5fjxjihqbqcuqgwbu

Pathway and network analysis of cancer genomes

2015 Nature Methods  
HyperModules was applied to the kinase-signaling network in ovarian cancer and revealed network modules with mutations in phosphorylation sites and kinase domains that significantly correlated with patient  ...  The HyperModules method 47 identifies subnetworks with cancer mutations that are maximally correlated with clinical characteristics such as patient survival, tumor stage or relapse.  ...  competinG Financial interests The authors declare no competing financial interests. reprints and permissions information is available online at http://www.nature. com/reprints/index.html.  ... 
doi:10.1038/nmeth.3440 pmid:26125594 pmcid:PMC4717906 fatcat:qxeg5bsmufdubboiqdp2bfn2eu

Computational methods and opportunities for phosphorylation network medicine

Yian Ann Chen, Steven A Eschrich
2014 Translational Cancer Research  
Kinase inhibitors are being regularly used in clinics for cancer treatment.  ...  With the increasing understanding of the complexity and redundancy of cell signaling, there is a growing recognition that targeting the entire network or system could be a necessary and advantageous strategy  ...  Special thanks to the phosphoproteomics research group at the Moffitt Cancer Center: Eric Haura, John Koomen, Uwe Rix, and Keiran Smalley. We also thank Alvaro  ... 
pmid:25530950 pmcid:PMC4271781 fatcat:bbfxl2kggzcvfowfn6fmlvrqnu