ScREMOTE: Using multimodal single cell data to predict regulatory gene relationships and to build a computational cell reprogramming model.

ABSTRACT: Cell reprogramming offers a potential treatment to many diseases, by regenerating specialized somatic cells. Despite decades of research, discovering the transcription factors that promote cell reprogramming has largely been accomplished through trial and error, a time-consuming and costly method. A computational model for cell reprogramming, however, could guide the hypothesis formulation and experimental validation, to efficiently utilize time and resources. Current methods often cannot account for the heterogeneity observed in cell reprogramming, or they only make short-term predictions, without modelling the entire reprogramming process. Here, we present scREMOTE, a novel computational model for cell reprogramming that leverages single cell multiomics data, enabling a more holistic vie

SUBMITTER: Tran A 

PROVIDER: S-EPMC8923006 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature