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GenSSI: a software toolbox for structural identifiability analysis of biological models

机译:GenSSI:用于生物学模型结构识别性分析的软件工具箱

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摘要

Summary: 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.
机译:简介:数学建模在系统生物学中具有关键作用。模型构建通常被认为是涉及多个任务的迭代循环,其中从一组特定的实验数据中估计模型的未知参数至关重要。参数估计的问题有很多可能的陷阱,建模人员应该非常小心避免它们。许多这样的困难源于基本的(但经常被忽略)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,任何试探性模型的结构可识别性都应在模型构建循环的开始时进行检查。但是,为任意非线性动态模型检查此属性并非易事。在这里,我们介绍了一个软件工具箱GenSSI(用于测试结构可识别性的生成系列),该工具箱使非专家用户可以进行这种分析。该工具箱在流行的MATLAB环境下运行,并附带详细的文档和相关示例。

著录项

  • 来源
    《Bioinformatics》 |2011年第18期|p.2610-2611|共2页
  • 作者

    Eva Balsa-Canto;

  • 作者单位
  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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