Chaouiya Claudine, Bérenguier Duncan, Keating Sarah M, Naldi Aurélien, van Iersel Martijn P, Rodriguez Nicolas, Dräger Andreas, Büchel Finja, Cokelaer Thomas, Kowal Bryan, Wicks Benjamin, Gonçalves Emanuel, Dorier Julien, Page Michel, Monteiro Pedro T, von Kamp Axel, Xenarios Ioannis, de Jong Hidde, Hucka Michael, Klamt Steffen, Thieffry Denis, Le Novère Nicolas, Saez-Rodriguez Julio, Helikar Tomáš
Instituto Gulbenkian de Ciência, Rua da Quinta Grande 6, 2780-156 Oeiras, Portugal.
BMC Syst Biol. 2013 Dec 10;7:135. doi: 10.1186/1752-0509-7-135.
Qualitative frameworks, especially those based on the logical discrete formalism, are increasingly used to model regulatory and signalling networks. A major advantage of these frameworks is that they do not require precise quantitative data, and that they are well-suited for studies of large networks. While numerous groups have developed specific computational tools that provide original methods to analyse qualitative models, a standard format to exchange qualitative models has been missing.
We present the Systems Biology Markup Language (SBML) Qualitative Models Package ("qual"), an extension of the SBML Level 3 standard designed for computer representation of qualitative models of biological networks. We demonstrate the interoperability of models via SBML qual through the analysis of a specific signalling network by three independent software tools. Furthermore, the collective effort to define the SBML qual format paved the way for the development of LogicalModel, an open-source model library, which will facilitate the adoption of the format as well as the collaborative development of algorithms to analyse qualitative models.
SBML qual allows the exchange of qualitative models among a number of complementary software tools. SBML qual has the potential to promote collaborative work on the development of novel computational approaches, as well as on the specification and the analysis of comprehensive qualitative models of regulatory and signalling networks.
定性框架,尤其是基于逻辑离散形式主义的框架,越来越多地用于对调控网络和信号网络进行建模。这些框架的一个主要优点是它们不需要精确的定量数据,并且非常适合大型网络的研究。虽然许多研究团队已经开发了特定的计算工具,提供了分析定性模型的原始方法,但一直缺少一种用于交换定性模型的标准格式。
我们提出了系统生物学标记语言(SBML)定性模型包(“qual”),它是SBML Level 3标准的扩展,用于生物网络定性模型的计算机表示。我们通过三个独立的软件工具对特定信号网络进行分析,展示了通过SBML qual实现模型的互操作性。此外,定义SBML qual格式的共同努力为开源模型库LogicalModel的开发铺平了道路,这将促进该格式的采用以及用于分析定性模型的算法的协作开发。
SBML qual允许在许多互补的软件工具之间交换定性模型。SBML qual有潜力促进在新型计算方法开发以及调控网络和信号网络综合定性模型的规范与分析方面的协作工作。