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

Marco S. Nobile, Daniela Besozzi, Paolo Cazzaniga, Giancarlo Mauri, Dario Pescini

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

19 Citations (Scopus)

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).

Original languageEnglish
Title of host publicationGECCO'12 - Proceedings of the 14th International Conference on Genetic and Evolutionary Computation Companion
Place of PublicationNew York
PublisherAssociation for Computing Machinery, Inc
Pages1421-1422
Number of pages2
ISBN (Electronic)978-1-4503-1178-6
DOIs
Publication statusPublished - 20 Aug 2012
Externally publishedYes
Event14th International Conference on Genetic and Evolutionary Computation, GECCO'12 - Philadelphia, PA, United States
Duration: 7 Jul 201211 Jul 2012

Conference

Conference14th International Conference on Genetic and Evolutionary Computation, GECCO'12
CountryUnited States
CityPhiladelphia, PA
Period7/07/1211/07/12

Keywords

  • GPU computing
  • Parameter estimation
  • Particle swarm optimization
  • Systems biology
  • Tau leaping

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