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Parameter discovery in stochastic biological models using simulated annealing and statistical model checking
2014
International Journal of Bioinformatics Research and Applications
Stochastic models are increasingly used to study the behaviour of biochemical systems. While the structure of such models is often readily available from first principles, unknown quantitative features of the model are incorporated into the model as parameters. Algorithmic discovery of parameter values from experimentally observed facts remains a challenge for the computational systems biology community. We present a new parameter discovery algorithm that uses simulated annealing, sequential
doi:10.1504/ijbra.2014.062998
pmid:24989866
pmcid:PMC4438994
fatcat:br2druphvjea3bslzoh6ja63ky