Novel global sensitivity analysis methodology accounting for the crucial role of the distribution of input parameters: Application to systems biology models

International Journal of Robust and Nonlinear Control

Volumn 22, Issue 10, 2012, Pages 1082-1102

  Rodriguez Fernandez, Maria ^a,b   Banga, Julio R ^c   Doyle III, Francis J ^a,b  

^a University of California   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c INSTITUTO DE INVESTIGACIONES MARINAS   (Spain)

Author keywords

global sensitivity analysis; model identification; parameter distribution; parameter estimation; robustness; systems biology

Indexed keywords

BIOCHEMICAL PATHWAY; CALCULATED VALUES; ENVIRONMENTAL CONDITIONS; GLOBAL SENSITIVITY; GLOBAL SENSITIVITY ANALYSIS; INITIAL CONCENTRATION; INPUT PARAMETER; LIKELIHOOD FUNCTIONS; LOW PROBABILITY; MODEL IDENTIFICATION; MODEL PREDICTION; MULTIPLE SOURCE; NUMERICAL ACCURACY; PARAMETER DISTRIBUTIONS; PARAMETER SET; PARAMETER SPACES; SMALL PERTURBATIONS; SYSTEMS BIOLOGY;

NUMERICAL METHODS; PARAMETER ESTIMATION; ROBUSTNESS (CONTROL SYSTEMS); SENSITIVITY ANALYSIS; UNCERTAINTY ANALYSIS;

BIOLOGICAL SYSTEMS;

EID: 84861614446     PISSN: 10498923     EISSN: 10991239     Source Type: Journal    
DOI: 10.1002/rnc.2797     Document Type: Article

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