title: A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions.
abstract: 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.
authors.affiliation: Systems Biology Group, Max-Planck-Institut für Dynamik komplexer technischer Systeme, 39106 Magdeburg, Germany. kremling@mpi-magdeburg.mpg.de
authors.forename: Andreas
authors.initials: A
authors.lastname: Kremling
authors.forename: Sophia
authors.initials: S
authors.lastname: Fischer
authors.forename: Kapil
authors.initials: K
authors.lastname: Gadkar
authors.forename: Francis J
authors.initials: FJ
authors.lastname: Doyle
authors.forename: Thomas
authors.initials: T
authors.lastname: Sauter
authors.forename: Eric
authors.initials: E
authors.lastname: Bullinger
authors.forename: Frank
authors.initials: F
authors.lastname: Allgöwer
authors.forename: Ernst D
authors.initials: ED
authors.lastname: Gilles
mesh_terms: D000465:Algorithms; D001671:Biochemistry / Q000706:statistics & numerical data*; D001698:Biomedical Engineering; D019295:Computational Biology; D003198:Computer Simulation; D005796:Genes; D005818:Genetic Engineering / Q000379:methods*; D007700:Kinetics; D008957:Models, Genetic; D017711:Nonlinear Dynamics; D012107:Research Design; D012984:Software