StochDecomp-Matlab package for noise decomposition in stochastic biochemical systems
StochDecomp-Matlab package for noise decomposition in stochastic biochemical systems
复制标题
StochDecomp-Matlab 包用于随机生化系统中的噪声分解
DOI：
10.1093/bioinformatics/btt631
复制
发表时间：
2014
期刊：
影响因子：
5.8
通讯作者：
Jetka T
中科院分区：
文献类型：
--
作者：
Jetka T
动机：在细胞水平上，随机性是生化过程中不可或缺的一个方面。噪声如何进入和传播的生化系统的研究为我们提供了非平凡的见解随机性的起源，在总的，然而，他们构成了不同的理论analysis.Results拼凑：在这里，我们提出了一个灵活的和广泛适用的噪声分解工具，使我们能够计算的贡献，个人反应的总变异系统的输出。因此，利用该软件包，可以量化噪声如何进入生化系统并在其中传播。我们还证明和验证使用JAK-STAT信号通路的噪声贡献，从个人的反应，可以推断出数据实验数据沿着贝叶斯参数推断。该方法是基于线性噪声近似，这是假设提供一个合理的表示分析systems. Available和实施：http://sourceforge.net/p/stochdecomp/Contact:mkomor@ippt.gov.pl或m.stumpf@imperial.ac. uk补充信息：补充数据可在Bioinformaticsonline。
Motivation: Stochasticity is an indispensable aspect of biochemical processes at the cellular level. Studies on how the noise enters and propagates in biochemical systems provided us with non-trivial insights into the origins of stochasticity, in total, however, they constitute a patchwork of different theoretical analyses.Results: Here we present a flexible and widely applicable noise decomposition tool that allows us to calculate contributions of individual reactions to the total variability of a system’s output. With the package it is, therefore, possible to quantify how the noise enters and propagates in biochemical systems. We also demonstrate and exemplify using the JAK-STAT signalling pathway that the noise contributions resulting from individual reactions can be inferred from data experimental data along with Bayesian parameter inference. The method is based on the linear noise approximation, which is assumed to provide a reasonable representation of analyzed systems.Availability and implementation:http://sourceforge.net/p/stochdecomp/Contact:mkomor@ippt.gov.pl or m.stumpf@imperial.ac.ukSupplementary information:Supplementary data are available atBioinformaticsonline.