title: Model composition for macromolecular regulatory networks.
abstract: Models of regulatory networks become more difficult to construct and understand as they grow in size and complexity. Large models are usually built up from smaller models, representing subsets of reactions within the larger network. To assist modelers in this composition process, we present a formal approach for model composition, a wizard-style program for implementing the approach, and suggested language extensions to the Systems Biology Markup Language to support model composition. To illustrate the features of our approach and how to use the JigCell Composition Wizard, we build up a model of the eukaryotic cell cycle "engine" from smaller pieces.
authors.affiliation: Computational Sciences Center of Emphasis, Pfizer Global Research & Development, 620 Memorial Drive, Cambridge, MA 02139, USA. ranjit.randhawa@pfizer.com
authors.forename: Ranjit
authors.initials: R
authors.lastname: Randhawa
authors.forename: Clifford A
authors.initials: CA
authors.lastname: Shaffer
authors.forename: John J
authors.initials: JJ
authors.lastname: Tyson
mesh_terms: D000465:Algorithms; D002453:Cell Cycle / Q000502:physiology; D018844:Cyclin-Dependent Kinases / Q000378:metabolism*; D008954:Models, Biological; D015398:Signal Transduction / Q000502:physiology; D049490:Systems Biology / Q000379:methods*; D015003:Yeasts / Q000378:metabolism / Q000502:physiology
chemical_list: D018844:Cyclin-Dependent Kinases