I. Introduction
Single-cell RNA sequencing (SC-RNA-seq) technology has changed the landscape of systems biology. Traditionally, systems biology models biological processes from a set of interlinked biochemical reactions. Based on the dynamics of molecular reactions, systems biologists have established a group of ordinary differential equations (ODEs) to explore the dynamic properties and network structures of these signaling pathway systems [1]. Using SC-RNA-seq technology, the gene expression of a physiological priocess can be captured at the whole genome scale and single cell level for a large volume of cells. These newly available data present new challenges for systems biology: the modeling object has been extended from a single or several signaling pathways to the whole genome. Although computation technology has progressed significantly recently, it is still a daunting, if not impossible, task to model a dynamic system with more than 20,000 variables using a group of ODEs.