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A Benchmark for Methods in Reverse Engineering and Model Discrimination: Problem Formulation and Solutions
Author(s) -
Andreas Kremling,
Sophia Fischer,
Kapil Gadkar,
Francis J. Doyle,
Thomas Sauter,
Eric Bullinger,
Frank Allgöwer,
Ernst Dieter Gilles
Publication year - 2004
Publication title -
genome research
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 9.556
H-Index - 297
eISSN - 1549-5469
pISSN - 1088-9051
DOI - 10.1101/gr.1226004
Subject(s) - benchmark (surveying) , identifiability , reverse engineering , bioreactor , nonlinear system , experimental data , biology , biological system , estimation theory , computer science , biochemical engineering , algorithm , machine learning , mathematics , statistics , engineering , physics , botany , geodesy , quantum mechanics , programming language , geography
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.

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