Network-Based Integration of Disparate Omic Data To Identify "Silent Players" in Cancer.

ABSTRACT: Development of high-throughput monitoring technologies enables interrogation of cancer samples at various levels of cellular activity. Capitalizing on these developments, various public efforts such as The Cancer Genome Atlas (TCGA) generate disparate omic data for large patient cohorts. As demonstrated by recent studies, these heterogeneous data sources provide the opportunity to gain insights into the molecular changes that drive cancer pathogenesis and progression. However, these insights are limited by the vast search space and as a result low statistical power to make new discoveries. In this paper, we propose methods for integrating disparate omic data using molecular interaction networks, with a view to gaining mechanistic insights into the relationship between molecular changes at

SUBMITTER: Ruffalo M 

PROVIDER: S-EPMC4684294 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature