Literature DB >> 15342560

A benchmark for methods in reverse engineering and model discrimination: problem formulation and solutions.

Andreas Kremling1, Sophia Fischer, Kapil Gadkar, Francis J Doyle, Thomas Sauter, Eric Bullinger, Frank Allgöwer, Ernst D Gilles.   

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.

Mesh:

Year:  2004        PMID: 15342560      PMCID: PMC515324          DOI: 10.1101/gr.1226004

Source DB:  PubMed          Journal:  Genome Res        ISSN: 1088-9051            Impact factor:   9.043


  10 in total

1.  Genetic network inference: from co-expression clustering to reverse engineering.

Authors:  P D'haeseleer; S Liang; R Somogyi
Journal:  Bioinformatics       Date:  2000-08       Impact factor: 6.937

2.  The organization of metabolic reaction networks. III. Application for diauxic growth on glucose and lactose.

Authors:  A Kremling; K Bettenbrock; B Laube; K Jahreis; J W Lengeler; E D Gilles
Journal:  Metab Eng       Date:  2001-10       Impact factor: 9.783

3.  Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

Authors:  T Ideker; V Thorsson; J A Ranish; R Christmas; J Buhler; J K Eng; R Bumgarner; D R Goodlett; R Aebersold; L Hood
Journal:  Science       Date:  2001-05-04       Impact factor: 47.728

4.  Reverse engineering gene networks: integrating genetic perturbations with dynamical modeling.

Authors:  Jesper Tegner; M K Stephen Yeung; Jeff Hasty; James J Collins
Journal:  Proc Natl Acad Sci U S A       Date:  2003-05-01       Impact factor: 11.205

5.  Identification of nucleocytoplasmic cycling as a remote sensor in cellular signaling by databased modeling.

Authors:  I Swameye; T G Muller; J Timmer; O Sandra; U Klingmuller
Journal:  Proc Natl Acad Sci U S A       Date:  2003-01-27       Impact factor: 11.205

6.  Modular modeling of cellular systems with ProMoT/Diva.

Authors:  M Ginkel; A Kremling; T Nutsch; R Rehner; E D Gilles
Journal:  Bioinformatics       Date:  2003-06-12       Impact factor: 6.937

7.  Reverse engineering of regulatory networks: simulation studies on a genetic algorithm approach for ranking hypotheses.

Authors:  Dirk Repsilber; Hans Liljenström; Siv G E Andersson
Journal:  Biosystems       Date:  2002 Jun-Jul       Impact factor: 1.973

8.  Importance of input perturbations and stochastic gene expression in the reverse engineering of genetic regulatory networks: insights from an identifiability analysis of an in silico network.

Authors:  Daniel E Zak; Gregory E Gonye; James S Schwaber; Francis J Doyle
Journal:  Genome Res       Date:  2003-11       Impact factor: 9.043

9.  Parameter estimation in biochemical pathways: a comparison of global optimization methods.

Authors:  Carmen G Moles; Pedro Mendes; Julio R Banga
Journal:  Genome Res       Date:  2003-10-14       Impact factor: 9.043

10.  Optimal dynamic experiments for bioreactor model discrimination.

Authors:  M J Cooney; K A McDonald
Journal:  Appl Microbiol Biotechnol       Date:  1995-10       Impact factor: 4.813

  10 in total
  36 in total

1.  Efficient classification of complete parameter regions based on semidefinite programming.

Authors:  Lars Kuepfer; Uwe Sauer; Pablo A Parrilo
Journal:  BMC Bioinformatics       Date:  2007-01-15       Impact factor: 3.169

2.  Approaches to biosimulation of cellular processes.

Authors:  F J Bruggeman; H V Westerhoff
Journal:  J Biol Phys       Date:  2006-11-11       Impact factor: 1.365

3.  Cutting the wires: modularization of cellular networks for experimental design.

Authors:  Moritz Lang; Sean Summers; Jörg Stelling
Journal:  Biophys J       Date:  2014-01-07       Impact factor: 4.033

4.  Cell-cell interaction networks regulate blood stem and progenitor cell fate.

Authors:  Daniel C Kirouac; Gerard J Madlambayan; Mei Yu; Edward A Sykes; Caryn Ito; Peter W Zandstra
Journal:  Mol Syst Biol       Date:  2009-07-28       Impact factor: 11.429

5.  On validation and invalidation of biological models.

Authors:  James Anderson; Antonis Papachristodoulou
Journal:  BMC Bioinformatics       Date:  2009-05-07       Impact factor: 3.169

6.  An iterative identification procedure for dynamic modeling of biochemical networks.

Authors:  Eva Balsa-Canto; Antonio A Alonso; Julio R Banga
Journal:  BMC Syst Biol       Date:  2010-02-17

7.  Towards a rigorous assessment of systems biology models: the DREAM3 challenges.

Authors:  Robert J Prill; Daniel Marbach; Julio Saez-Rodriguez; Peter K Sorger; Leonidas G Alexopoulos; Xiaowei Xue; Neil D Clarke; Gregoire Altan-Bonnet; Gustavo Stolovitzky
Journal:  PLoS One       Date:  2010-02-23       Impact factor: 3.240

8.  Discriminating between rival biochemical network models: three approaches to optimal experiment design.

Authors:  Bence Mélykúti; Elias August; Antonis Papachristodoulou; Hana El-Samad
Journal:  BMC Syst Biol       Date:  2010-04-01

9.  A model invalidation-based approach for elucidating biological signalling pathways, applied to the chemotaxis pathway in R. sphaeroides.

Authors:  Mark A J Roberts; Elias August; Abdullah Hamadeh; Philip K Maini; Patrick E McSharry; Judith P Armitage; Antonis Papachristodoulou
Journal:  BMC Syst Biol       Date:  2009-10-31

10.  Developing optimal input design strategies in cancer systems biology with applications to microfluidic device engineering.

Authors:  Filippo Menolascina; Domenico Bellomo; Thomas Maiwald; Vitoantonio Bevilacqua; Caterina Ciminelli; Angelo Paradiso; Stefania Tommasi
Journal:  BMC Bioinformatics       Date:  2009-10-15       Impact factor: 3.169

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.