A Dataset of Benchmark Boolean Models for Gene Regulatory Networks

Gene regulatory networks (GRNs) capture the processes involved in gene regulation. Boolean network (BN) modeling provides a simple but effective framework for understanding the dynamical behavior of GRNs. Although BNs have been widely studied and applied, algorithms and theoretical analyses are usually tested on ad hoc selected or artificially constructed models, which may introduce bias and fail to capture the essential structural and dynamical properties of real GRNs for which they are ultimately intended. Benchmarking offers standardized models for validation and comparison of computational methods and analyses. We construct benchmark BN models for GRNs of four major biological kingdoms: animals, bacteria, fungi, and plants. All models are built from empirically observed recurrent properties and motifs in GRNs. The proposed benchmark BNs provide a systematical and unbiased basis for evaluating algorithms and theoretical analyses.