Comparison of discrete- and continuous-state stochastic methods to model neuronal signal transduction

2010 ACM International Conference on Bioinformatics and Computational Biology, ACM-BCB 2010

Volumn , Issue , 2010, Pages 394-397

  Manninen, Tiina ^a   Keller, Daniel X ^b  

^a TAMPERE UNIVERSITY OF TECHNOLOGY   (Finland)

^b EPFL   (Switzerland)

Author keywords

Chemical langevin equation; Gillespie stochastic simulation algorithm; Signal transduction; Stochastic differential equation

Indexed keywords

BIOCHEMICAL REACTIONS; CHEMICAL LANGEVIN EQUATION; CHEMICAL SPECIES; COMPUTATION TIME; COMPUTING SOLUTIONS; HYBRID DETERMINISTIC; REACTION METHOD; SIGNAL TRANSDUCTION NETWORKS; STOCHASTIC DIFFERENTIAL EQUATION MODELS; STOCHASTIC DIFFERENTIAL EQUATIONS; STOCHASTIC METHODS; STOCHASTIC SIMULATION ALGORITHMS; TEST CASE;

ALGORITHMS; BACTERIOPHAGES; BIOINFORMATICS; COMPUTER SIMULATION; DAMAGE DETECTION; DIFFERENTIAL EQUATIONS; GRID COMPUTING; MEASUREMENT THEORY; SIGNAL TRANSDUCTION; STOCHASTIC SYSTEMS;

STOCHASTIC MODELS;

EID: 77958042740     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/1854776.1854838     Document Type: Conference Paper

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