Chaouiya Claudine, Keating Sarah M, Berenguier Duncan, Naldi Aurélien, Thieffry Denis, van Iersel Martijn P, Le Novère Nicolas, Helikar Tomáš
J Integr Bioinform. 2015 Sep 4;12(2):270. doi: 10.2390/biecoll-jib-2015-270.
Quantitative methods for modelling biological networks require an in-depth knowledge of the biochemical reactions and their stoichiometric and kinetic parameters. In many practical cases, this knowledge is missing. This has led to the development of several qualitative modelling methods using information such as, for example, gene expression data coming from functional genomic experiments. The SBML Level 3 Version 1 Core specification does not provide a mechanism for explicitly encoding qualitative models, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactical constructs. The SBML Qualitative Models package for SBML Level 3 adds features so that qualitative models can be directly and explicitly encoded. The approach taken in this package is essentially based on the definition of regulatory or influence graphs. The SBML Qualitative Models package defines the structure and syntax necessary to describe qualitative models that associate discrete levels of activities with entity pools and the transitions between states that describe the processes involved. This is particularly suited to logical models (Boolean or multi-valued) and some classes of Petri net models can be encoded with the approach.
用于生物网络建模的定量方法需要对生化反应及其化学计量和动力学参数有深入了解。在许多实际情况中，这种知识是缺失的。这促使人们开发了几种定性建模方法，这些方法利用诸如来自功能基因组实验的基因表达数据等信息。SBML Level 3版本1核心规范没有提供显式编码定性模型的机制，但它确实为SBML包提供了一种扩展核心规范并添加额外语法结构的机制。用于SBML Level 3的SBML定性模型包增加了一些功能，以便可以直接和显式地编码定性模型。此包中采用的方法本质上基于调控或影响图的定义。SBML定性模型包定义了描述定性模型所需的结构和语法，这些定性模型将离散的活动水平与实体池以及描述所涉及过程状态之间的转换相关联。这特别适用于逻辑模型（布尔或多值），并且某些类别的Petri网模型可以用这种方法进行编码。
