title: Dizzy: stochastic simulation of large-scale genetic regulatory networks.
abstract: We describe Dizzy, a software tool for stochastically and deterministically modeling the spatially homogeneous kinetics of integrated large-scale genetic, metabolic, and signaling networks. Notable features include a modular simulation framework, reusable modeling elements, complex kinetic rate laws, multi-step reaction processes, steady-state noise estimation, and spatial compartmentalization.
authors.affiliation: Institute for Systems Biology, 1441 North 34th Street, Seattle, Washington 98103-8904, USA.
authors.forename: Stephen
authors.initials: S
authors.lastname: Ramsey
authors.forename: David
authors.initials: D
authors.lastname: Orrell
authors.forename: Hamid
authors.initials: H
authors.lastname: Bolouri
mesh_terms: D000465:Algorithms; D002468:Cell Physiological Phenomena; D003198:Computer Simulation; D005786:Gene Expression Regulation / Q000502:physiology*; D007700:Kinetics; D008954:Models, Biological; D015233:Models, Statistical; D009097:Multienzyme Complexes / Q000378:metabolism; D011506:Proteins / Q000378:metabolism*; D015398:Signal Transduction / Q000502:physiology*; D012984:Software; D013269:Stochastic Processes; D014584:User-Computer Interface
chemical_list: D009097:Multienzyme Complexes; D011506:Proteins