Gene regulatory network inference during cell fate decisions by perturbation strategies.

ABSTRACT: With rapid advances in biological technology and computational approaches, inferring specific gene regulatory networks from data alone during cell fate decisions, including determining direct regulations and their intensities between biomolecules, remains one of the most significant challenges. In this study, we propose a general computational approach based on systematic perturbation, statistical, and differential analyses to infer network topologies and identify network differences during cell fate decisions. For each cell fate state, we first theoretically show how to calculate local response matrices based on perturbation data under systematic perturbation analysis, and we also derive the wild-type (WT) local response matrix for specific ordinary differential equations. To make the inf

SUBMITTER: Hu Q 

PROVIDER: S-EPMC11876352 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature