High-performance single-cell gene regulatory network inference at scale: the Inferelator 3.0

• DOI: 10.1093/bioinformatics/btac117
• Publication Date: 2022-02-17T20:12:10Z
• Authors: Claudia Skok Gibbs; Christopher A Jac...; Giuseppe-Antonio ...; Andreas Tjärnberg; Aashna Shah; Aaron Watters; Nicholas De Veaux; Konstantine Tchou...; Ren Yi; Tymor Hamamsy; Dayanne M Castro; Nicholas Carriero; Bram L Gorissen; David Gresham; Emily R Miraldi; Richard Bonneau
• Keywords: Gene regulatory network; Functional Genomics

Gene regulatory networks define relationships between transcription factors and target genes within a biological system, reconstructing them is essential for understanding cellular growth function. Methods inferring from genomics data have evolved rapidly over the last decade in response to advances sequencing technology machine learning. The scale of collection has increased dramatically; largest genome-wide gene expression datasets grown thousands measurements millions single cells, new technologies are on horizon increase tens cells above.