Computational modeling of the EGF-receptor system: a paradigm for systems biology

Computational models have rarely been used as tools by biologists but, when models provide experimentally testable predictions, they can be extremely useful. The epidermal growth factor receptor (EGFR) is probably the best-understood receptor system, and computational models have played a significan...

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Bibliographic Details
Published in:Trends in cell biology 2003, Vol.13 (1), p.43-50
Main Authors: Steven Wiley, H, Shvartsman, Stanislav Y, Lauffenburger, Douglas A
Format: Article
Language:English
Subjects:
Animals
Computational Biology - methods
Computational Biology - trends
Humans
Models, Biological
Protein Binding - physiology
Receptor, Epidermal Growth Factor - chemistry
Receptor, Epidermal Growth Factor - metabolism
Signal Transduction - physiology
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Summary:Computational models have rarely been used as tools by biologists but, when models provide experimentally testable predictions, they can be extremely useful. The epidermal growth factor receptor (EGFR) is probably the best-understood receptor system, and computational models have played a significant part in its elucidation. For many years, models have been used to analyze EGFR dynamics and to interpret mutational studies, and are now being used to understand processes including signal transduction, autocrine loops and developmental patterning. The success of EGFR modeling can be a guide to combining models and experiments productively to understand complex biological processes as integrated systems.
ISSN:0962-8924
1879-3088
DOI:10.1016/S0962-8924(02)00009-0