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一种有效的 HIV/AIDS 模型参数可识别性自动检测程序。

An effective automatic procedure for testing parameter identifiability of HIV/AIDS models.

机构信息

Department of Information Engineering, University of Padova, Italy.

出版信息

Bull Math Biol. 2011 Aug;73(8):1734-53. doi: 10.1007/s11538-010-9588-2. Epub 2010 Oct 17.

Abstract

Realistic HIV models tend to be rather complex and many recent models proposed in the literature could not yet be analyzed by traditional identifiability testing techniques. In this paper, we check a priori global identifiability of some of these nonlinear HIV models taken from the recent literature, by using a differential algebra algorithm based on previous work of the author. The algorithm is implemented in a software tool, called DAISY (Differential Algebra for Identifiability of SYstems), which has been recently released (DAISY is freely available on the web site http://www.dei.unipd.it/~pia/ ). The software can be used to automatically check global identifiability of (linear and) nonlinear models described by polynomial or rational differential equations, thus providing a general and reliable tool to test global identifiability of several HIV models proposed in the literature. It can be used by researchers with a minimum of mathematical background.

摘要

真实的 HIV 模型往往比较复杂,而文献中提出的许多最近的模型还不能用传统的可识别性测试技术进行分析。在本文中,我们使用基于作者先前工作的微分代数算法,对一些来自最近文献的非线性 HIV 模型进行了先验全局可识别性检查。该算法在一个名为 DAISY(系统可识别性的微分代数)的软件工具中实现,该工具最近已发布(可在网站 http://www.dei.unipd.it/~pia/ 上免费获得 DAISY)。该软件可用于自动检查由多项式或有理微分方程描述的(线性和)非线性模型的全局可识别性,从而为文献中提出的几个 HIV 模型的全局可识别性测试提供了一种通用且可靠的工具。它可以被具有最小数学背景的研究人员使用。

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