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CERENA:化学反应网络分析仪——用于随机化学动力学模拟与分析的工具箱。

CERENA: ChEmical REaction Network Analyzer--A Toolbox for the Simulation and Analysis of Stochastic Chemical Kinetics.

作者信息

Kazeroonian Atefeh, Fröhlich Fabian, Raue Andreas, Theis Fabian J, Hasenauer Jan

机构信息

Institute of Computational Biology, Helmholtz Zentrum München-German Research Center for Environmental Health, Neuherberg, Germany.

Department of Mathematics, Chair of Mathematical Modeling of Biological Systems, Technische Universität München, Garching, Germany.

出版信息

PLoS One. 2016 Jan 25;11(1):e0146732. doi: 10.1371/journal.pone.0146732. eCollection 2016.

Abstract

Gene expression, signal transduction and many other cellular processes are subject to stochastic fluctuations. The analysis of these stochastic chemical kinetics is important for understanding cell-to-cell variability and its functional implications, but it is also challenging. A multitude of exact and approximate descriptions of stochastic chemical kinetics have been developed, however, tools to automatically generate the descriptions and compare their accuracy and computational efficiency are missing. In this manuscript we introduced CERENA, a toolbox for the analysis of stochastic chemical kinetics using Approximations of the Chemical Master Equation solution statistics. CERENA implements stochastic simulation algorithms and the finite state projection for microscopic descriptions of processes, the system size expansion and moment equations for meso- and macroscopic descriptions, as well as the novel conditional moment equations for a hybrid description. This unique collection of descriptions in a single toolbox facilitates the selection of appropriate modeling approaches. Unlike other software packages, the implementation of CERENA is completely general and allows, e.g., for time-dependent propensities and non-mass action kinetics. By providing SBML import, symbolic model generation and simulation using MEX-files, CERENA is user-friendly and computationally efficient. The availability of forward and adjoint sensitivity analyses allows for further studies such as parameter estimation and uncertainty analysis. The MATLAB code implementing CERENA is freely available from http://cerenadevelopers.github.io/CERENA/.

摘要

基因表达、信号转导以及许多其他细胞过程都受到随机波动的影响。对这些随机化学动力学进行分析,对于理解细胞间变异性及其功能影响十分重要,但同时也具有挑战性。尽管已经开发出了众多随机化学动力学的精确和近似描述方法,但仍缺少能够自动生成这些描述并比较其准确性和计算效率的工具。在本论文中,我们介绍了CERENA,这是一个用于使用化学主方程解统计近似来分析随机化学动力学的工具箱。CERENA实现了随机模拟算法以及用于过程微观描述的有限状态投影、用于中观和宏观描述的系统规模扩展和矩方程,还有用于混合描述的新型条件矩方程。在单个工具箱中提供这种独特的描述集合,便于选择合适的建模方法。与其他软件包不同,CERENA的实现完全通用,例如允许使用时间相关的倾向和非质量作用动力学。通过提供SBML导入、符号模型生成以及使用MEX文件进行模拟,CERENA用户友好且计算效率高。前向和伴随灵敏度分析的可用性使得能够进行诸如参数估计和不确定性分析等进一步研究。实现CERENA的MATLAB代码可从http://cerenadevelopers.github.io/CERENA/免费获取。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/71c9/4726759/530faaefb11e/pone.0146732.g001.jpg

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