Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression.

ABSTRACT: Cells respond to environmental and developmental stimuli by remodeling their transcriptomes through regulation of both mRNA transcription and mRNA decay. A central goal of biology is identifying the global set of regulatory relationships between factors that control mRNA production and degradation and their target transcripts and construct a predictive model of gene expression. Regulatory relationships are typically identified using transcriptome measurements and causal inference algorithms. RNA kinetic parameters are determined experimentally by employing run-on or metabolic labeling (e.g. 4-thiouracil) methods that allow transcription and decay rates to be separately measured. Here, we develop a deep learning model, trained with single-cell RNA-seq data, that both infers causal regulator

SUBMITTER: Jackson CA 

PROVIDER: S-EPMC10542544 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature