Multiscale learning of gene network-driven phenotypic dynamics of single cells (opens in new tab)

Understanding how gene regulatory networks (GRNs) dynamically orchestrate cell fate emergence remains a fundamental challenge. Here, we present GRNvelo, a computational framework that reconstructs multiscale cell fate dynamics by integrating GRNs with phenotypic dynamics from temporal single-cell RNA-seq data. GRNvelo establishes a biologically interpretable and mathematically rigorous multiscale model that couples GRN-driven single-cell velocity with nonlocal cell growth-mediated population ...