Fused Regression for Multi-source Gene Regulatory Network Inference.

ABSTRACT: Understanding gene regulatory networks is critical to understanding cellular differentiation and response to external stimuli. Methods for global network inference have been developed and applied to a variety of species. Most approaches consider the problem of network inference independently in each species, despite evidence that gene regulation can be conserved even in distantly related species. Further, network inference is often confined to single data-types (single platforms) and single cell types. We introduce a method for multi-source network inference that allows simultaneous estimation of gene regulatory networks in multiple species or biological processes through the introduction of priors based on known gene relationships such as orthology incorporated using fused regression. Thi

SUBMITTER: Lam KY 

PROVIDER: S-EPMC5140053 | biostudies-literature | 2016 Dec

REPOSITORIES: biostudies-literature