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Gene regulatory networks are powerful tools for modeling interactions amonggenes to regulate their expression for homeostasis and differentiation.Single-cell sequencing offers a unique opportunity to build these networks withhigh-resolution data. There are many proposed computational methods to buildthese networks using single-cell data and different approaches are followed tobenchmark these methods. In this review, we lay the basic terminology in thefield and define the success metrics. Next, we present an overview ofapproaches for benchmarking computational gene regulatory network approachesfor building gene regulatory networks and point out gaps and future directionsin this regard.

Approaches for benchmarking single-cell gene regulatory network inference methods