Gene regulatory network inference from single-cell data using optimal transport#

Authors#

François Lamoline, Isabel Haasler, Johan Karlsson, Jorge Goncalves, Atte Aalto

Abstract#

Modelling gene expression is a central problem in systems biology. Single-cell technolo- gies have revolutionised the field by enabling sequencing at the resolution of individual cells. This results in a much richer data compared to what is obtained by bulk technologies, offering new possibilities and challenges for gene regulatory network inference. Here we introduce GRIT — a method to fit a differential equation model and to infer gene regulatory networks from single-cell data using the theory of optimal transport. The idea consists in tracking the evolution of the cell distribution over time and finding the system that min- imises the transport cost between consecutive time points.