YAMONES: A Computational Architecture for Molecular Network Simulation

Abstract

One of the most important challenges for Bioinformatics is the simulation of a single cell, even if we restrict ourselves to simple models of the molecular networks responsible for the behavior of organisms. The challenge involves not only the development of experimental techniques to obtain kinetic parameters that characterize the myriad reactions occurring inside cells, but also computational approaches able to simulate and test the complex models generated. These systems have stochastic behavior; they can take different paths depending on environmental conditions. We can describe them using stochastic models that have a high computational cost, but the simulations can be performed efficiently on distributed architectures like grids and clusters of computers. In this work we describe an implementation of a computational architecture to execute this kind of large scale simulation using a grid infrastructure. We validate the proposed architecture using experiments in order to estimate its performance.