We present a parameter estimation method, based on particle swarm optimization (PSO) and embedding the tauleaping 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 multiswarm formulation of PSO. The whole method is developed for GPGPU architecture to reduce the computational costs. Copyright is held by the author/owner(s)
Nobile, M., Besozzi, D., Cazzaniga, P., Mauri, G., Pescini, D. (2012). Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs. In GECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion (pp.1421-1422). Association for Computing Machinery [10.1145/2330784.2330964].
Estimating reaction constants in stochastic biological systems with a multi-swarm PSO running on GPUs
NOBILE, MARCO SALVATORE;BESOZZI, DANIELA;MAURI, GIANCARLO;PESCINI, DARIO
2012
Abstract
We present a parameter estimation method, based on particle swarm optimization (PSO) and embedding the tauleaping 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 multiswarm formulation of PSO. The whole method is developed for GPGPU architecture to reduce the computational costs. Copyright is held by the author/owner(s)
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