Identification of periodic attractors in Boolean networks using a priori information.

ABSTRACT: Boolean networks (BNs) have been developed to describe various biological processes, which requires analysis of attractors, the long-term stable states. While many methods have been proposed to detection and enumeration of attractors, there are no methods which have been demonstrated to be theoretically better than the naive method and be practically used for large biological BNs. Here, we present a novel method to calculate attractors based on a priori information, which works much and verifiably faster than the naive method. We apply the method to two BNs which differ in size, modeling formalism, and biological scope. Despite these differences, the method presented here provides a powerful tool for the analysis of both networks. First, our analysis of a BN studying the effect of the micr

SUBMITTER: Munzner U 

PROVIDER: S-EPMC8803189 | biostudies-literature | 2022 Jan

REPOSITORIES: biostudies-literature