Revealing Pathway Dynamics in Heart Diseases by Analyzing Multiple Differential Networks.

ABSTRACT: Development of heart diseases is driven by dynamic changes in both the activity and connectivity of gene pathways. Understanding these dynamic events is critical for understanding pathogenic mechanisms and development of effective treatment. Currently, there is a lack of computational methods that enable analysis of multiple gene networks, each of which exhibits differential activity compared to the network of the baseline/healthy condition. We describe the iMDM algorithm to identify both unique and shared gene modules across multiple differential co-expression networks, termed M-DMs (multiple differential modules). We applied iMDM to a time-course RNA-Seq dataset generated using a murine heart failure model generated on two genotypes. We showed that iMDM achieves higher accuracy in inferr

SUBMITTER: Ma X 

PROVIDER: S-EPMC4471235 | biostudies-literature | 2015 Jun

REPOSITORIES: biostudies-literature