Simulating and Coarse-graining Complex Biological Systems with NFsim

Simulating and Coarse-graining Complex Biological Systems with NFsim Michael Sneddon

Abstract: Managing the overwhelming numbers of molecular states and interactions is a fundamental obstacle in building predictive models of biological systems. The Network-Free Stochastic Simulator (NFsim) is a general-purpose modeling platform that overcomes the combinatorial nature of molecular interactions. Unlike standard simulation approaches, NFsim uses a biologically intuitive representation based on molecular objects with binding and modification sites acted on by reaction rules. Rules operate on molecular objects directly to produce exact stochastic results without ever expanding the system into equations. As a result, NFsim performance is independent of the size of the reaction network. In addition, rate laws can be defined as mathematical or conditional functions of individual molecular states enabling advanced model coarse-graining and allowing users to merge Boolean and kinetic representations. NFsim opens the door to modeling new classes of systems that were previously inaccessible to general-purpose simulators. This tutorial session will introduce NFsim and illustrate its capabilities with models of immune system signaling, microbial signaling, and cytoskeletal assembly.

Download at http://emonet.biology.yale.edu/nfsim/

Supported by NSF

NFsim was developed by Michael Sneddon^1,2, James R. Faeder³ and Thierry Emonet^1,2,4

¹Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, CT 06520- 8103, USA. ²Interdepartmental Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06511, USA. ³Department of Computational Biology, University of Pittsburgh School of Medicine, Pittsburgh, PA 15260, USA. ⁴Department of Physics, Yale University, New Haven, CT 06520- 8103, USA