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Title: ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks

Abstract

Stochastic simulation and modeling play an important role to elucidate the fundamental mechanisms in complex biochemical networks. The parametric sensitivity analysis of reaction networks becomes a powerful mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, due to overwhelming computational cost, parametric sensitivity analysis is a extremely challenging problem for stochastic models with a high-dimensional parameter space and for which existing approaches are very slow. Here we present an information-theoretic sensitivity analysis in path-space (ISAP) MATLAB package that simulates stochastic processes with various algorithms and most importantly implements a gradient-free approach to quantify the parameter sensitivities of stochastic chemical reaction network dynamics using the pathwise Fisher information matrix (PFIM; Pantazis, Katsoulakis, and Vlachos 2013). The sparse, block-diagonal structure of the PFIM makes its computational complexity scale linearly with the number of model parameters. As a result of the gradientfree and the sparse nature of the PFIM, it is highly suitable for the sensitivity analysis of stochastic reaction networks with a very large number of model parameters, which are typical in the modeling and simulation of complex biochemical phenomena. Finally, the PFIM provides a fast sensitivity screening method (Arampatzis, Katsoulakis, and Pantazis 2015) whichmore » allows it to be combined with any existing sensitivity analysis software.« less

Authors:
 [1];  [1];  [1]
  1. Univ. of Massachusetts, Amherst, MA (United States)
Publication Date:
Research Org.:
Univ. of Massachusetts, Amherst, MA (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21); Defense Advanced Research Projects Agency (DARPA) (United States)
OSTI Identifier:
1509830
Grant/Contract Number:  
SC0010723; W911NF1520122
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Statistical Software
Additional Journal Information:
Journal Volume: 85; Journal Issue: 3; Journal ID: ISSN 1548-7660
Publisher:
Foundation for Open Access Statistics
Country of Publication:
United States
Language:
English
Subject:
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CHEMISTRY; stochastic biochemical networks; parametric sensitivity analysis; high-dimensional parameter space; pathwise Fisher information matrix; fast sensitivity screening

Citation Formats

Hu, Weilong, Pantazis, Yannis, and Katsoulakis, Markos A. ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks. United States: N. p., 2018. Web. doi:10.18637/jss.v085.i03.
Hu, Weilong, Pantazis, Yannis, & Katsoulakis, Markos A. ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks. United States. doi:10.18637/jss.v085.i03.
Hu, Weilong, Pantazis, Yannis, and Katsoulakis, Markos A. Thu . "ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks". United States. doi:10.18637/jss.v085.i03. https://www.osti.gov/servlets/purl/1509830.
@article{osti_1509830,
title = {ISAP-MATLAB Package for Sensitivity Analysis of High-Dimensional Stochastic Chemical Networks},
author = {Hu, Weilong and Pantazis, Yannis and Katsoulakis, Markos A.},
abstractNote = {Stochastic simulation and modeling play an important role to elucidate the fundamental mechanisms in complex biochemical networks. The parametric sensitivity analysis of reaction networks becomes a powerful mathematical and computational tool, yielding information regarding the robustness and the identifiability of model parameters. However, due to overwhelming computational cost, parametric sensitivity analysis is a extremely challenging problem for stochastic models with a high-dimensional parameter space and for which existing approaches are very slow. Here we present an information-theoretic sensitivity analysis in path-space (ISAP) MATLAB package that simulates stochastic processes with various algorithms and most importantly implements a gradient-free approach to quantify the parameter sensitivities of stochastic chemical reaction network dynamics using the pathwise Fisher information matrix (PFIM; Pantazis, Katsoulakis, and Vlachos 2013). The sparse, block-diagonal structure of the PFIM makes its computational complexity scale linearly with the number of model parameters. As a result of the gradientfree and the sparse nature of the PFIM, it is highly suitable for the sensitivity analysis of stochastic reaction networks with a very large number of model parameters, which are typical in the modeling and simulation of complex biochemical phenomena. Finally, the PFIM provides a fast sensitivity screening method (Arampatzis, Katsoulakis, and Pantazis 2015) which allows it to be combined with any existing sensitivity analysis software.},
doi = {10.18637/jss.v085.i03},
journal = {Journal of Statistical Software},
number = 3,
volume = 85,
place = {United States},
year = {2018},
month = {9}
}

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