stochdecomp matlab package for noise decomposition in stochastic biochemical systems

• DOI: 10.48550/arxiv.1308.3103
• Publication Date: 2013-11-04
• Authors: Tomasz Jetka; Anna Gambin; Michał Komorowski; Agata Charzyńska; Michael P. H. Stumpf
• Keywords: 0301 basic medicine; Stochastic Processes; 0303 health sciences; Biochemical Phenomena; Molecular Networks (q-bio.MN); Bayes Theorem; Quantitative Biology - Quantitative Methods; STAT Transcription Factors; 03 medical and health sciences; FOS: Biological sciences; Quantitative Biology - Molecular Networks; Software; Quantitative Methods (q-bio.QM); Janus Kinases

Abstract 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: [e-mail] or [e-mail] Supplementary information: Supplementary data are available at Bioinformatics online.