Urbanczik Robert
Institute of Pharmacology, University of Bern, Friedbühlstr. 49, CH-3010 Bern, Switzerland.
BMC Bioinformatics. 2006 Mar 13;7:129. doi: 10.1186/1471-2105-7-129.
Despite recent algorithmic and conceptual progress, the stoichiometric network analysis of large metabolic models remains a computationally challenging problem.
SNA is a interactive, high performance toolbox for analysing the possible steady state behaviour of metabolic networks by computing the generating and elementary vectors of their flux and conversions cones. It also supports analysing the steady states by linear programming. The toolbox is implemented mainly in Mathematica and returns numerically exact results. It is available under an open source license from: http://bioinformatics.org/project/?group_id=546.
Thanks to its performance and modular design, SNA is demonstrably useful in analysing genome scale metabolic networks. Further, the integration into Mathematica provides a very flexible environment for the subsequent analysis and interpretation of the results.
尽管最近在算法和概念方面取得了进展，但大型代谢模型的化学计量网络分析仍然是一个计算上具有挑战性的问题。
SNA是一个交互式的高性能工具箱，用于通过计算代谢网络通量和转化锥的生成向量和基本向量来分析其可能的稳态行为。它还支持通过线性规划分析稳态。该工具箱主要用Mathematica实现，并返回数值精确的结果。可从以下开源许可获取：http://bioinformatics.org/project/?group_id=546。
由于其性能和模块化设计，SNA在分析基因组规模代谢网络方面显然很有用。此外，集成到Mathematica中为后续结果的分析和解释提供了非常灵活的环境。
