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Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm by Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence is a scholarly article available to read on EtoBox.

What is Continuous time Boolean modeling for biological signaling: application of Gillespie algorithm about?

This article presents an algorithm that allows modeling of biological networks in a qualitative framework with continuous time. Mathematical modeling is used as a systems biology tool to answer biological questions, and more precisely, to validate a network that describes biological observations and to predict the effect of perturbations. We propose a modeling approach that is intrinsically continuous in time. The algorithm presented here fills the gap between qualitative and quantitative modeling. It is based on continuous time Markov process applied on a Boolean state space. In order to describe the temporal evolution, we explicitly specify the transition rates for each node. For that purpose, we built a language that can be seen as a generalization of Boolean equations. The values of transition rates have a natural interpretation: it is the inverse of the time for the transition to occur. Mathematically, this approach can be translated in a set of ordinary differential equations on probability distributions; therefore, it can be seen as an approach in between quantitative and qualitative. We developed a C++ software, MaBoSS, that is able to simulate such a system by applying Kin

Author

Stoll, Gautier; Viara, Eric; Barillot, Emmanuel; Calzone, Laurence

Published

2012

Language

EN