BoolNet–an R package for generation, reconstruction and analysis of Boolean networks. Bioinformatics 2010;26(10):1378–80

Motivation: As the study of information processing in living cells moves from individual pathways to complex regulatory networks, mathematical models and simulation become indispensable tools for analyzing the complex behaviour of such networks and can provide deep insights into the functioning of cells. The dynamics of gene expression, for example, can be modeled with Boolean networks. These are mathematical models of low complexity, but have the advantage of being able to capture essential properties of gene-regulatory networks. However, current implementations of Boolean networks only focus on different sub-aspects of this model and do not allow for a seamless integration into existing pre-processing pipelines. Results: BoolNet efficiently integrates methods for synchronous, asynchronous, and probabilistic Boolean networks. This includes reconstructing networks from time series, generating random networks, robustness analysis via perturbation, Markov chain simulations, and identification and visualization of attractors. Availability: The package BoolNet is freely available from the