Inference of a Boolean Network From Causal Logic Implications.

ABSTRACT: Biological systems contain a large number of molecules that have diverse interactions. A fruitful path to understanding these systems is to represent them with interaction networks, and then describe flow processes in the network with a dynamic model. Boolean modeling, the simplest discrete dynamic modeling framework for biological networks, has proven its value in recapitulating experimental results and making predictions. A first step and major roadblock to the widespread use of Boolean networks in biology is the laborious network inference and construction process. Here we present a streamlined network inference method that combines the discovery of a parsimonious network structure and the identification of Boolean functions that determine the dynamics of the system. This inference meth

SUBMITTER: Maheshwari P 

PROVIDER: S-EPMC9246059 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature