Estimating genome-wide regulatory activity from multi-omics data sets using mathematical optimization.

ABSTRACT:

Background

Gene regulation is one of the most important cellular processes, indispensable for the adaptability of organisms and closely interlinked with several classes of pathogenesis and their progression. Elucidation of regulatory mechanisms can be approached by a multitude of experimental methods, yet integration of the resulting heterogeneous, large, and noisy data sets into comprehensive and tissue or disease-specific cellular models requires rigorous computational methods. Recently, several algorithms have been proposed which model genome-wide gene regulation as sets of (linear) equations over the activity and relationships of transcription factors, genes and other factors. Subsequent optimization finds those parameters that minimize the divergence of predicted and measured

SUBMITTER: Trescher S 

PROVIDER: S-EPMC5369021 | biostudies-literature | 2017 Mar

REPOSITORIES: biostudies-literature