Literature DB >> 17591178

Optimal experimental design in an epidermal growth factor receptor signalling and down-regulation model.

F P Casey1, D Baird, Q Feng, R N Gutenkunst, J J Waterfall, C R Myers, K S Brown, R A Cerione, J P Sethna.   

Abstract

We apply the methods of optimal experimental design to a differential equation model for epidermal growth factor receptor signalling, trafficking and down-regulation. The model incorporates the role of a recently discovered protein complex made up of the E3 ubiquitin ligase, Cbl, the guanine exchange factor (GEF), Cool-1 (beta -Pix) and the Rho family G protein Cdc42. The complex has been suggested to be important in disrupting receptor down-regulation. We demonstrate that the model interactions can accurately reproduce the experimental observations, that they can be used to make predictions with accompanying uncertainties, and that we can apply ideas of optimal experimental design to suggest new experiments that reduce the uncertainty on unmeasurable components of the system.

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Year:  2007        PMID: 17591178     DOI: 10.1049/iet-syb:20060065

Source DB:  PubMed          Journal:  IET Syst Biol        ISSN: 1751-8849            Impact factor:   1.615


  26 in total

1.  Reply to Comment on "Sloppy models, parameter uncertainty, and the role of experimental design"

Authors:  David R Hagen; Joshua F Apgar; David K Witmer; Forest M White; Bruce Tidor
Journal:  Mol Biosyst       Date:  2011-08-01

2.  Cellular level models as tools for cytokine design.

Authors:  Mala L Radhakrishnan; Bruce Tidor
Journal:  Biotechnol Prog       Date:  2010 Jul-Aug

3.  Sloppy models, parameter uncertainty, and the role of experimental design.

Authors:  Joshua F Apgar; David K Witmer; Forest M White; Bruce Tidor
Journal:  Mol Biosyst       Date:  2010-06-17

4.  Ensembles of signal transduction models using Pareto Optimal Ensemble Techniques (POETs).

Authors:  Sang Ok Song; Anirikh Chakrabarti; Jeffrey D Varner
Journal:  Biotechnol J       Date:  2010-07       Impact factor: 4.677

5.  A protocol for dynamic model calibration.

Authors:  Alejandro F Villaverde; Dilan Pathirana; Fabian Fröhlich; Jan Hasenauer; Julio R Banga
Journal:  Brief Bioinform       Date:  2022-01-17       Impact factor: 11.622

6.  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

Review 7.  Studying Cellular Signal Transduction with OMIC Technologies.

Authors:  Benjamin D Landry; David C Clarke; Michael J Lee
Journal:  J Mol Biol       Date:  2015-08-03       Impact factor: 5.469

8.  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

9.  Optimal experimental design for parameter estimation of a cell signaling model.

Authors:  Samuel Bandara; Johannes P Schlöder; Roland Eils; Hans Georg Bock; Tobias Meyer
Journal:  PLoS Comput Biol       Date:  2009-11-06       Impact factor: 4.475

10.  Trajectory-oriented Bayesian experiment design versus Fisher A-optimal design: an in depth comparison study.

Authors:  Patrick Weber; Andrei Kramer; Clemens Dingler; Nicole Radde
Journal:  Bioinformatics       Date:  2012-09-15       Impact factor: 6.937

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