The systems biology simulation core algorithm.

Roland Keller,Michael J Ziller,Nicolas Le Novère,Akito Tabira,Hannes Planatscher,Alexander Dörr,Andreas Dräger,Akira Funahashi,Noriko Hiroi,Richard Adams,Nicolas Rodriguez,Andreas Zell

doi:10.1186/1752-0509-7-55

Abstract

BackgroundWith the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases.ResultsThis article describes an efficient algorithm to solve SBML models that are interpreted in terms of ordinary differential equations. We begin our consideration with a formal representation of the mathematical form of the models and explain all parts of the algorithm in detail, including several preprocessing steps. We provide a flexible reference implementation as part of the Systems Biology Simulation Core Library, a community-driven project providing a large collection of numerical solvers and a sophisticated interface hierarchy for the definition of custom differential equation systems. To demonstrate the capabilities of the new algorithm, it has been tested with the entire SBML Test Suite and all models of BioModels Database.ConclusionsThe formal description of the mathematics behind the SBML format facilitates the implementation of the algorithm within specifically tailored programs. The reference implementation can be used as a simulation backend for Java™-based programs. Source code, binaries, and documentation can be freely obtained under the terms of the LGPL version 3 from http://simulation-core.sourceforge.net. Feature requests, bug reports, contributions, or any further discussion can be directed to the mailing list simulation-core-development@lists.sourceforge.net.

Highlights

With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology
In order to derive an algorithm for the interpretation of Systems Biology Markup Language (SBML) models in a differential equation framework, it is first necessary to take a closer look at the mathematical equations implied by this data format
Based on this general description, we will discuss all necessary steps to deduce an algorithm that takes all special cases for the various levels and versions of SBML into account

Summary

Introduction

With the increasing availability of high dimensional time course data for metabolites, genes, and fluxes, the mathematical description of dynamical systems has become an essential aspect of research in systems biology. Models are often encoded in formats such as SBML, whose structure is very complex and difficult to evaluate due to many special cases. Ambitious national and international research projects such as the Virtual Liver Network [2] strive to derive even organ-wide models of biological systems that include all kinds of processes taking place at several levels of detail. The exchange, storage, interoperability, and the XML-based standard description formats such as the Systems Biology Markup Language (SBML) [7,8] and CellML [9,10] enable encoding of quantitative biological network models. Software libraries for reading and manipulating the content of these formats are available [13,14,15] as well as end-user programs supporting these model description languages

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