Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs

Authors:
Marco S. Nobile;Daniela Besozzi;Paolo Cazzaniga;Giancarlo Mauri;Dario Pescini
Affiliations:
Università degli Studi di Milano-Bicocca, Milano, Italy;Università degli Studi di Milano, Milano, Italy;Università degli Studi di Bergamo, Bergamo, Italy;Università degli Studi di Milano-Bicocca, Milano, Italy;Università degli Studi di Milano-Bicocca, Milano, Italy
Venue:
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Year:
2012

Citing 1
Cited 1

A GPU-Based multi-swarm PSO method for parameter estimation in stochastic biological systems exploiting discrete-time target series

EvoBIO'12 Proceedings of the 10th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Mining for variability in the coagulation pathway: a systems biology approach

EvoBIO'13 Proceedings of the 11th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

Quantified Score

Hi-index	0.00

Visualization

Abstract

We present a parameter estimation method, based on particle swarm optimization (PSO) and embedding the tau-leaping algorithm, for the efficient estimation of reaction constants in stochastic models of biological systems, using as target a set of discrete-time measurements of molecular amounts sampled in different experimental conditions. To account for the multiplicity of data, we consider a multi-swarm formulation of PSO. The whole method is developed for GPGPU architecture to reduce the computational costs.