SABRE: A Tool for Stochastic Analysis of Biochemical Reaction Networks

TL;DR

SABRE is a computational tool that efficiently analyzes biochemical reaction networks using stochastic and deterministic methods, enabling detailed transient analysis of biological systems modeled as Markov chains.

Contribution

Introduces SABRE, a novel tool implementing fast adaptive uniformization for stochastic analysis and mean-field approximation for deterministic analysis of biochemical networks.

Findings

SABRE effectively computes transient solutions of biochemical networks.

The tool supports both stochastic and deterministic analyses.

Case studies demonstrate SABRE's practical utility.

Abstract

The importance of stochasticity within biological systems has been shown repeatedly during the last years and has raised the need for efficient stochastic tools. We present SABRE, a tool for stochastic analysis of biochemical reaction networks. SABRE implements fast adaptive uniformization (FAU), a direct numerical approximation algorithm for computing transient solutions of biochemical reaction networks. Biochemical reactions networks represent biological systems studied at a molecular level and these reactions can be modeled as transitions of a Markov chain. SABRE accepts as input the formalism of guarded commands, which it interprets either as continuous-time or as discrete-time Markov chains. Besides operating in a stochastic mode, SABRE may also perform a deterministic analysis by directly computing a mean-field approximation of the system under study. We illustrate the different functionalities of SABRE by means of biological case studies.