Reducing Boolean networks with backward equivalence.

ABSTRACT:

Background

Boolean Networks (BNs) are a popular dynamical model in biology where the state of each component is represented by a variable taking binary values that express, for instance, activation/deactivation or high/low concentrations. Unfortunately, these models suffer from the state space explosion, i.e., there are exponentially many states in the number of BN variables, which hampers their analysis.

Results

We present Boolean Backward Equivalence (BBE), a novel reduction technique for BNs which collapses system variables that, if initialized with same value, maintain matching values in all states. A large-scale validation on 86 models from two online model repositories reveals that BBE is effective, since it is able to reduce more than 90% of the models. Furthermore, o

SUBMITTER: Argyris GA 

PROVIDER: S-EPMC10207686 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature