Figure 1 .

The overall workflow of GRN inference methods. The methods start with filtering genes based on their variability or a priori knowledge. They next construct intermediate data depending on the modeling and data assumption and then infer the network. The output of these methods can be either co-expression networks which are undirected from top selected connections or directed networks with regulatory relationships between genes. To evaluate the constructed networks, each method adopts different validation techniques, including using simulation, enrichment analysis, literature support, and expert interpretation and conducting additional laboratory experiments.