(Bio)Process Engineering Group, Spanish National Research Council, IIM-CSIC, 36208 Vigo, Spain.
Bioinformatics. 2011 Sep 15;27(18):2610-1. doi: 10.1093/bioinformatics/btr431. Epub 2011 Jul 22.
Mathematical modeling has a key role in systems biology. Model building is often regarded as an iterative loop involving several tasks, among which the estimation of unknown parameters of the model from a certain set of experimental data is of central importance. This problem of parameter estimation has many possible pitfalls, and modelers should be very careful to avoid them. Many of such difficulties arise from a fundamental (yet often overlooked) property: the so-called structural (or a priori) identifiability, which considers the uniqueness of the estimated parameters. Obviously, the structural identifiability of any tentative model should be checked at the beginning of the model building loop. However, checking this property for arbitrary non-linear dynamic models is not an easy task. Here we present a software toolbox, GenSSI (Generating Series for testing Structural Identifiability), which enables non-expert users to carry out such analysis. The toolbox runs under the popular MATLAB environment and is accompanied by detailed documentation and relevant examples.
The GenSSI toolbox and the related documentation are available at http://www.iim.csic.es/%7Egenssi.
数学建模在系统生物学中起着关键作用。模型构建通常被认为是一个迭代循环，涉及多个任务，其中从给定的实验数据集中估计模型的未知参数至关重要。参数估计这个问题可能存在许多陷阱，建模者应该非常小心地避免这些陷阱。许多此类困难源于一个基本的（但往往被忽视的）特性：所谓的结构（或先验）可识别性，它考虑了估计参数的唯一性。显然，在模型构建循环的开始就应该检查任何暂定模型的结构可识别性。然而，对于任意非线性动态模型，检查该属性并不是一项简单的任务。在这里，我们提出了一个软件工具箱 GenSSI（用于测试结构可识别性的生成序列），它允许非专业用户进行这样的分析。该工具箱在流行的 MATLAB 环境下运行，并附有详细的文档和相关示例。
GenSSI 工具箱及相关文档可在 http://www.iim.csic.es/~genssi 上获得。
