TSMiner: a novel framework for generating time-specific gene regulatory networks from time-series expression profiles.

ABSTRACT: Time-series gene expression profiles are the primary source of information on complicated biological processes; however, capturing dynamic regulatory events from such data is challenging. Herein, we present a novel analytic tool, time-series miner (TSMiner), that can construct time-specific regulatory networks from time-series expression profiles using two groups of genes: (i) genes encoding transcription factors (TFs) that are activated or repressed at a specific time and (ii) genes associated with biological pathways showing significant mutual interactions with these TFs. Compared with existing methods, TSMiner demonstrated superior sensitivity and accuracy. Additionally, the application of TSMiner to a time-course RNA-seq dataset associated with mouse liver regeneration (LR) identified

SUBMITTER: Han M 

PROVIDER: S-EPMC8502000 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature