An ensemble of models of the acute inflammatory response to bacterial lipopolysaccharide in rats: results from parameter space reduction

DOI10.1016/j.jtbi.2008.04.033zbMath1398.92053OpenAlexW2127260736WikidataQ60154142 ScholiaQ60154142MaRDI QIDQ1796361

Yanyan Li

Publication date: 17 October 2018

Published in: Journal of Theoretical Biology (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jtbi.2008.04.033

zbMATH Keywords

dynamical systemsmodel identificationcytokinescompensatory mechanismsensemble of models

Mathematics Subject Classification ID

Classification and discrimination; cluster analysis (statistical aspects) (62H30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Physiology (general) (92C30)

Related Items

A practical approach to parameter estimation applied to model predicting heart rate regulation ⋮ Global sensitivity analysis of a mathematical model of acute inflammation identifies nonlinear dependence of cumulative tissue damage on host interleukin-6 responses ⋮ A `portfolio of model approximations' approach to understanding invasion success with vector-borne disease ⋮ CE-PLoc: An ensemble classifier for predicting protein subcellular locations by fusing different modes of pseudo amino acid composition ⋮ A mathematical model of pulmonary gas exchange under inflammatory stress ⋮ Mathematical modeling of energy consumption in the acute inflammatory response ⋮ Parameter subset selection techniques for problems in mathematical biology ⋮ Mechanistic simulations of inflammation: current state and future prospects ⋮ A data-driven model of the role of energy in sepsis ⋮ On the Importance of the Jacobian Determinant in Parameter Inference for Random Parameter and Random Measurement Error Models ⋮ The inverse problem in mathematical biology

Uses Software

• fminsearch
• DAISY

Cites Work

• Identification of parametric models from experimental data. Transl. from an upd. French version by the authors, with the help of John Norton
• Numerical parameter identifiability and estimability: Integrating identifiability, estimability, and optimal sampling design
• Hierarchical clustering schemes
• Convergence Properties of the Nelder--Mead Simplex Method in Low Dimensions