Paper Info
Title
Workshop: Algorithms for discovery of mutated pathways in cancer
Abstract
We apply our algorithms to several cancer types including glioblastoma multiforme (GBM), lung adenocarcinoma, and ovarian carcinoma (OV). HotNet identifies significant subnetworks that are part of well-known cancer pathways as well as novel subnetworks. Among the most significant subnetworks identified in OV data is the Notch signaling pathway, and this result appears in the first TCGA OV publication [1]. We also extend HotNet to identify mutated pathways associated with patient survival [2]. In the TCGA OV data, we discover 9 subnetworks containing genes whose mutations are associated with survival. Genes in 4 of these subnetworks overlap pathways known to be associated to survival, including focal adhesion and cell adhesion pathways. In GBM and lung Dendrix finds significant sets of genes that are mutated in large subsets of patients and whose mutations are approximately exclusive, including genes in well known cancer pathways (e.g., Rb1 and p53 pathways).
Year
DOI
Venue
2012
10.1109/ICCABS.2012.6182678
ICCABS
Keywords
Field
DocType
Markov processes,Monte Carlo methods,adhesion,cancer,cellular biophysics,genetics,GBM,HotNet,Markov chain Monte Carlo algorithm,Notch signaling pathway,cancer pathways,cell adhesion pathways,focal adhesion,genes,glioblastoma multiforme,lung Dendrix,lung adenocarcinoma,mutated pathways,ovarian carcinoma,patient survival,Markov chain Monte Carlo,cancer genomics,diffusion processes,driver pathways,networks
Gene,Glioblastoma,Biology,Focal adhesion,Algorithm,Cell adhesion,Adenocarcinoma,Notch signaling pathway,Bioinformatics,Cancer,Carcinoma
Conference
Citations 
PageRank 
References 
0
0.34
3
Authors
3
Name
Order
Citations
PageRank
Fabio Vandin121827.55
Eli Upfal24310743.13
Benjamin J. Raphael342951.53