Design of In Silico Experiments as a Tool for Nonlinear Sensitivity Analysis of Knowledge-Driven Models-Reference-Cited by-同舟云学术

Design of In Silico Experiments as a Tool for Nonlinear Sensitivity Analysis of Knowledge-Driven Models

Published:2014-03-13 Issue:18 Volume:53 Page:7517-7525
ISSN:0888-5885
Container-title:Industrial & Engineering Chemistry Research
language:en
Short-container-title:Ind. Eng. Chem. Res.

Author:

Kiparissides Alexandros¹,Georgakis Christos²,Mantalaris Athanasios¹,Pistikopoulos Efstratios N.¹

Affiliation:

1. Biological Systems Engineering Laboratory, Centre for Process Systems Engineering, Imperial College, London SW7 2AZ, United Kingdom

2. System Research Institute for Chemical & Biological Processes and Department of Chemical & Biological Engineering, Tufts University, Medford, Massachusetts 02155, United States

Publisher

American Chemical Society (ACS)

Subject

Industrial and Manufacturing Engineering,General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/ie4032154

Reference25 articles.

1. ‘Closing the loop’ in biological systems modeling — From the in silico to the in vitro

2. Sensitivity analysis of model output

3. Global Sensitivity Analysis Challenges in Biological Systems Modeling

4. Global sensitivity indices for nonlinear mathematical models and their Monte Carlo estimates

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