{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T12:32:32Z","timestamp":1767961952408,"version":"3.49.0"},"reference-count":6,"publisher":"Oxford University Press (OUP)","issue":"5","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2012,3,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Motivation: The growing interest in the role of stochasticity in biochemical systems drives the demand for tools to analyse stochastic dynamical models of chemical reactions. One powerful tool to elucidate performance of dynamical systems is sensitivity analysis. Traditionally, however, the concept of sensitivity has mainly been applied to deterministic systems, and the difficulty to generalize these concepts for stochastic systems results from necessity of extensive Monte Carlo simulations.<\/jats:p>\n               <jats:p>Results: Here we present a Matlab package, StochSens, that implements sensitivity analysis for stochastic chemical systems using the concept of the Fisher Information Matrix (FIM). It uses the linear noise approximation to represent the FIM in terms of solutions of ordinary differential equations. This is the first computational tool that allows for quick computation of the Information Matrix for stochastic systems without the need for Monte Carlo simulations.<\/jats:p>\n               <jats:p>Availability: \u00a0http:\/\/www.theosysbio.bio.ic.ac.uk\/resources\/stns<\/jats:p>\n               <jats:p>Supplementary information: \u00a0Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <jats:p>Contact: \u00a0mkomor@ippt.gov.pl; M.Stumpf@imperial.ac.uk<\/jats:p>","DOI":"10.1093\/bioinformatics\/btr714","type":"journal-article","created":{"date-parts":[[2012,2,29]],"date-time":"2012-02-29T09:41:36Z","timestamp":1330508496000},"page":"731-733","source":"Crossref","is-referenced-by-count":17,"title":["StochSens\u2014matlab package for sensitivity analysis of stochastic chemical systems"],"prefix":"10.1093","volume":"28","author":[{"given":"Micha\u0142","family":"Komorowski","sequence":"first","affiliation":[{"name":"Division of Molecular Biosciences, Imperial College London, London, UK"}]},{"given":"Justina","family":"\u017durauskien\u0117","sequence":"additional","affiliation":[{"name":"Division of Molecular Biosciences, Imperial College London, London, UK"}]},{"given":"Michael P.H.","family":"Stumpf","sequence":"additional","affiliation":[{"name":"Division of Molecular Biosciences, Imperial College London, London, UK"}]}],"member":"286","published-online":{"date-parts":[[2012,2,28]]},"reference":[{"key":"2023012512195018300_B1","doi-asserted-by":"crossref","first-page":"2530","DOI":"10.1529\/biophysj.104.053405","article-title":"Sensitivity analysis of discrete stochastic systems","volume":"88","author":"Gunawan","year":"2005","journal-title":"Biophysical J."},{"key":"2023012512195018300_B2","doi-asserted-by":"crossref","first-page":"8645","DOI":"10.1073\/pnas.1015814108","article-title":"Sensitivity, robustness, and identifiability in stochastic chemical kinetics models","volume":"108","author":"Komorowski","year":"2011","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"2023012512195018300_B3","doi-asserted-by":"crossref","first-page":"2037","DOI":"10.1093\/bioinformatics\/btn350","article-title":"Dynamical modeling and multi-experiment fitting with potterswheel","volume":"24","author":"Maiwald","year":"2008","journal-title":"Bioinformatics"},{"key":"2023012512195018300_B4","doi-asserted-by":"crossref","first-page":"S59","DOI":"10.1098\/rsif.2008.0084.focus","article-title":"Mapping global sensitivity of cellular network dynamics: sensitivity heat maps and a global summation Law","volume":"5","author":"Rand","year":"2008","journal-title":"J R Soc Interface"},{"key":"2023012512195018300_B5","doi-asserted-by":"crossref","first-page":"724","DOI":"10.1016\/j.jcp.2006.06.047","article-title":"Efficient stochastic sensitivity analysis of discrete event systems","volume":"221","author":"Plyasunov","year":"2007","journal-title":"J. Comput. 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