title: Efficient rejection-based simulation of biochemical reactions with stochastic noise and delays.
abstract: We propose a new exact stochastic rejection-based simulation algorithm for biochemical reactions and extend it to systems with delays. Our algorithm accelerates the simulation by pre-computing reaction propensity bounds to select the next reaction to perform. Exploiting such bounds, we are able to avoid recomputing propensities every time a (delayed) reaction is initiated or finished, as is typically necessary in standard approaches. Propensity updates in our approach are still performed, but only infrequently and limited for a small number of reactions, saving computation time and without sacrificing exactness. We evaluate the performance improvement of our algorithm by experimenting with concrete biological models.
authors.affiliation: The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068, Italy.
authors.forename: Vo Hong
authors.initials: VH
authors.lastname: Thanh
authors.affiliation: The Microsoft Research - University of Trento Centre for Computational and Systems Biology, Piazza Manifattura 1, Rovereto 38068, Italy.
authors.forename: Corrado
authors.initials: C
authors.lastname: Priami
authors.affiliation: Department of Mathematics, University of Trento, Italy.
authors.forename: Roberto
authors.initials: R
authors.lastname: Zunino
mesh_terms: D000465:Algorithms; D001669:Biochemical Phenomena; D003198:Computer Simulation; D005492:Folic Acid / Q000378:metabolism; D006801:Humans; D020935:MAP Kinase Signaling System; D008954:Models, Biological; D008956:Models, Chemical; D009369:Neoplasms / Q000378:metabolism; D013269:Stochastic Processes
chemical_list: D005492:Folic Acid