Literature DB >> 26085503

libRoadRunner: a high performance SBML simulation and analysis library.

Endre T Somogyi1, Jean-Marie Bouteiller2, James A Glazier1, Matthias König3, J Kyle Medley4, Maciej H Swat1, Herbert M Sauro4.   

Abstract

MOTIVATION: 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.
AVAILABILITY AND IMPLEMENTATION: 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. CONTACTS: hsauro@u.washington.edu or somogyie@indiana.edu SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online. Published by Oxford University Press 2015. This work is written by US Government employees and is in the public domain in the US.

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Mesh:

Year:  2015        PMID: 26085503      PMCID: PMC4607739          DOI: 10.1093/bioinformatics/btv363

Source DB:  PubMed          Journal:  Bioinformatics        ISSN: 1367-4803            Impact factor:   6.937


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