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首页> 外文期刊>Computational Biology and Bioinformatics, IEEE/ACM Transactions on >Fuzzy Logic as a Computational Tool for Quantitative Modelling of Biological Systems with Uncertain Kinetic Data
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Fuzzy Logic as a Computational Tool for Quantitative Modelling of Biological Systems with Uncertain Kinetic Data

机译：模糊逻辑作为具有不确定动力学数据的生物系统定量建模的计算工具

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摘要

Quantitative modelling of biological systems has become an indispensable computational approach in the design of novel and analysis of existing biological systems. However, kinetic data that describe the system’s dynamics need to be known in order to obtain relevant results with the conventional modelling techniques. These data are often hard or even impossible to obtain. Here, we present a quantitative fuzzy logic modelling approach that is able to cope with unknown kinetic data and thus produce relevant results even though kinetic data are incomplete or only vaguely defined. Moreover, the approach can be used in the combination with the existing quantitative modelling techniques only in certain parts of the system, i.e., where kinetic data are missing. The case study of the approach proposed here is performed on the model of three-gene repressilator.
机译：生物系统的定量建模已成为小说设计和现有生物系统分析中不可缺少的计算方法。但是，需要知道描述系统动力学的动力学数据，以便使用常规建模技术获得相关结果。这些数据通常很难获得甚至无法获得。在这里，我们提出了一种定量模糊逻辑建模方法，该方法能够处理未知的动力学数据，因此即使动力学数据不完整或定义模糊，也可以产生相关结果。此外，该方法只能与系统中的某些部分，即缺少动力学数据的部分，与现有的定量建模技术结合使用。本文提出的方法的案例研究是在三基因再加压器模型上进行的。

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