A comprehensive survey of regulatory network inference methods using single cell RNA sequencing data.

ABSTRACT: Gene regulatory network is a complicated set of interactions between genetic materials, which dictates how cells develop in living organisms and react to their surrounding environment. Robust comprehension of these interactions would help explain how cells function as well as predict their reactions to external factors. This knowledge can benefit both developmental biology and clinical research such as drug development or epidemiology research. Recently, the rapid advance of single-cell sequencing technologies, which pushed the limit of transcriptomic profiling to the individual cell level, opens up an entirely new area for regulatory network research. To exploit this new abundant source of data and take advantage of data in single-cell resolution, a number of computational methods have be

SUBMITTER: Nguyen H 

PROVIDER: S-EPMC8138892 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature