Network-Based Interpretation of Diverse High-Throughput Datasets through the Omics Integrator Software Package.

ABSTRACT: High-throughput, 'omic' methods provide sensitive measures of biological responses to perturbations. However, inherent biases in high-throughput assays make it difficult to interpret experiments in which more than one type of data is collected. In this work, we introduce Omics Integrator, a software package that takes a variety of 'omic' data as input and identifies putative underlying molecular pathways. The approach applies advanced network optimization algorithms to a network of thousands of molecular interactions to find high-confidence, interpretable subnetworks that best explain the data. These subnetworks connect changes observed in gene expression, protein abundance or other global assays to proteins that may not have been measured in the screens due to inherent bias or noise in me

SUBMITTER: Tuncbag N 

PROVIDER: S-EPMC4838263 | biostudies-literature | 2016 Apr

REPOSITORIES: biostudies-literature