Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood

Raue, Andreas; Kreutz, Clemens; Maiwald, Tim; Bachmann, Jasmin; Schilling, Marcel; Klingmüller, Ursula; Timmer, Jens

doi:10.1093/bioinformatics/btp358

Public

Structural and practical identifiability analysis of partially observed dynamical models by exploiting the profile likelihood

Published in Bioinformatics • Jun 8, 2009

Authors:

Andreas Raue

Clemens Kreutz

Tim Maiwald

Abstract

MOTIVATION: Mathematical description of biological reaction networks by differential equations leads to large models whose parameters are calibrated in order to optimally explain experimental data. Often only parts of the model can be observed directly. Given a model that sufficiently describes the ...

Subject

Identifiability

Computer science

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