Computing hierarchical transition graphs of asynchronous genetic regulatory networks

In the field of theoretical biology the study of the dynamics of the so-called gene regulatory networks is useful to follow the relationship between the expression of a gene and its dynamic regulatory effect on the cell fate. To date, most of the models developed for this purpose, applies the synchronous update schedule while reality is far from being so. On the other hand, the more realistic asynchronous update requires to compute all possible updates at each single instant, thus bearing a much greater computational load. In the present work, we describe a novel method that addresses the problem of efficiently exploring the dynamics of a gene regulatory network with the asynchronous update.