title: libRoadRunner: a high performance SBML simulation and analysis library.
abstract: BACKGROUND
  This article presents libRoadRunner, an extensible, high-performance, cross-platform, open-source software library for the simulation and analysis of models expressed using Systems Biology Markup Language (SBML). SBML is the most widely used standard for representing dynamic networks, especially biochemical networks. libRoadRunner is fast enough to support large-scale problems such as tissue models, studies that require large numbers of repeated runs and interactive simulations.
  
  
  RESULTS
  libRoadRunner is a self-contained library, able to run both as a component inside other tools via its C++ and C bindings, and interactively through its Python interface. Its Python Application Programming Interface (API) is similar to the APIs of MATLAB ( WWWMATHWORKSCOM: ) and SciPy ( HTTP//WWWSCIPYORG/: ), making it fast and easy to learn. libRoadRunner uses a custom Just-In-Time (JIT) compiler built on the widely used LLVM JIT compiler framework. It compiles SBML-specified models directly into native machine code for a variety of processors, making it appropriate for solving extremely large models or repeated runs. libRoadRunner is flexible, supporting the bulk of the SBML specification (except for delay and non-linear algebraic equations) including several SBML extensions (composition and distributions). It offers multiple deterministic and stochastic integrators, as well as tools for steady-state analysis, stability analysis and structural analysis of the stoichiometric matrix.
  
  
  METHODS
  libRoadRunner binary distributions are available for Mac OS X, Linux and Windows. The library is licensed under Apache License Version 2.0. libRoadRunner is also available for ARM-based computers such as the Raspberry Pi. http://www.libroadrunner.org provides online documentation, full build instructions, binaries and a git source repository.
  
  
  BACKGROUND
  hsauro@u.washington.edu or somogyie@indiana.edu
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Biocomplexity Institute and Department of Physics, Indiana University, Bloomington, IN, 47405, USA.
authors.forename: Endre T
authors.initials: ET
authors.lastname: Somogyi
authors.affiliation: Biomedical Engineering Department, University of Southern California, Los Angeles, CA, 90089, USA.
authors.forename: Jean-Marie
authors.initials: JM
authors.lastname: Bouteiller
authors.affiliation: Biocomplexity Institute and Department of Physics, Indiana University, Bloomington, IN, 47405, USA.
authors.forename: James A
authors.initials: JA
authors.lastname: Glazier
authors.affiliation: Department of Computational Systems Biochemistry, University Medicine Charité Berlin, 10117, Berlin, Germany and.
authors.forename: Matthias
authors.initials: M
authors.lastname: König
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
authors.forename: J Kyle
authors.initials: JK
authors.lastname: Medley
authors.affiliation: Biocomplexity Institute and Department of Physics, Indiana University, Bloomington, IN, 47405, USA.
authors.forename: Maciej H
authors.initials: MH
authors.lastname: Swat
authors.affiliation: Department of Bioengineering, University of Washington, Seattle, WA 98195, USA.
authors.forename: Herbert M
authors.initials: HM
authors.lastname: Sauro
mesh_terms: D002448:Cell Adhesion / Q000502:physiology; D003198:Computer Simulation; D006801:Humans; D008099:Liver / Q000378:metabolism; D008954:Models, Biological; D008962:Models, Theoretical; D009474:Neurons / Q000378:metabolism; D011381:Programming Languages; D012984:Software; D049490:Systems Biology / Q000379:methods*