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Article (Périodiques scientifiques)
A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions.
Kremling, Andreas; Fischer, Sophia; Gadkar, Kapil et al.
2004In Genome Research, 14 (9), p. 1773-85
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Mots-clés :
Algorithms; Biochemistry/statistics & numerical data; Biomedical Engineering; Computational Biology; Computer Simulation; Genes; Genetic Engineering/methods; Kinetics; Models, Genetic; Nonlinear Dynamics; Research Design; Software
Résumé :
[en] A benchmark problem is described for the reconstruction and analysis of biochemical networks given sampled experimental data. The growth of the organisms is described in a bioreactor in which one substrate is fed into the reactor with a given feed rate and feed concentration. Measurements for some intracellular components are provided representing a small biochemical network. Problems of reverse engineering, parameter estimation, and identifiability are addressed. The contribution mainly focuses on the problem of model discrimination. If two or more model variants describe the available experimental data, a new experiment must be designed to discriminate between the hypothetical models. For the problem presented, the feed rate and feed concentration of a bioreactor system are available as control inputs. To verify calculated input profiles an interactive Web site (http://www.sysbio.de/projects/benchmark/) is provided. Several solutions based on linear and nonlinear models are discussed.
Disciplines :
Sciences du vivant: Multidisciplinaire, généralités & autres
Auteur, co-auteur :
Kremling, Andreas
Fischer, Sophia
Gadkar, Kapil
Doyle, Francis J.
SAUTER, Thomas ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Life Science Research Unit
Bullinger, Eric
Allgower, Frank
Gilles, Ernst D.
Langue du document :
Anglais
Titre :
A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions.
Date de publication/diffusion :
2004
Titre du périodique :
Genome Research
ISSN :
1088-9051
eISSN :
1549-5469
Maison d'édition :
Cold Spring Harbor Laboratory Press, Etats-Unis - New York
Volume/Tome :
14
Fascicule/Saison :
9
Pagination :
1773-85
Peer reviewed :
Peer reviewed vérifié par ORBi
Disponible sur ORBilu :
depuis le 26 avril 2013

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