title: StochSens--Matlab package for sensitivity analysis of stochastic chemical systems.
abstract: BACKGROUND
  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.
  
  
  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.
  
  
  BACKGROUND
  http://www.theosysbio.bio.ic.ac.uk/resources/stns
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Division of Molecular Biosciences, Imperial College London, London, UK. mkomor@ippt.gov.pl
authors.forename: Michal
authors.initials: M
authors.lastname: Komorowski
authors.forename: Justina
authors.initials: J
authors.lastname: Zurauskiene
authors.forename: Michael P H
authors.initials: MP
authors.lastname: Stumpf
mesh_terms: D000465:Algorithms; D004798:Enzymes / Q000737:chemistry; D015870:Gene Expression; D007700:Kinetics; D015233:Models, Statistical; D012984:Software
chemical_list: D004798:Enzymes