title: Adaptive deployment of model reductions for tau-leaping simulation.
abstract: Multiple time scales in cellular chemical reaction systems often render the tau-leaping algorithm inefficient. Various model reductions have been proposed to accelerate tau-leaping simulations. However, these are often identified and deployed manually, requiring expert knowledge. This is time-consuming and prone to error. In previous work, we proposed a methodology for automatic identification and validation of model reduction opportunities for tau-leaping simulation. Here, we show how the model reductions can be automatically and adaptively deployed during the time course of a simulation. For multiscale systems, this can result in substantial speedups.
authors.affiliation: Department of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, USA.
authors.forename: Sheng
authors.initials: S
authors.lastname: Wu
authors.affiliation: Department of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, USA.
authors.forename: Jin
authors.initials: J
authors.lastname: Fu
authors.affiliation: Department of Computer Science, University of California Santa Barbara, Santa Barbara, California 93106, USA.
authors.forename: Linda R
authors.initials: LR
authors.lastname: Petzold
mesh_terms: D003198:Computer Simulation; D004583:Electrons; D005557:Formaldehyde / Q000737:chemistry; D008962:Models, Theoretical; D013057:Spectrum Analysis
chemical_list: D005557:Formaldehyde