Document Detail

Multiple attractors in immunology: theory and experiment.
MedLine Citation:
PMID:  9652095     Owner:  NLM     Status:  MEDLINE    
This selective survey discusses the relative merits of various modeling approaches in immunology that exhibit multiple attractors, and also assesses the ability of the different models to contribute to deeper biological understanding. The first topic is global anti-idiotypic network models, which, like Hopfield neural network models, exhibit a large number of steady states that are identified with memory. It is shown that a 'reverse engineering approach' to T-cell vaccination for autoimmunity, featuring steady states corresponding respectively to 'normality', 'vaccination' and 'disease', is able to spur new experiments, in spite of the model's deliberate neglect of almost all biological detail. Mention is made of several other T-cell models that feature bistability for Th1 or Th2 dominance, or for activation and unresponsiveness.
L A Segel
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Publication Detail:
Type:  Journal Article; Research Support, Non-U.S. Gov't; Research Support, U.S. Gov't, Non-P.H.S.; Review    
Journal Detail:
Title:  Biophysical chemistry     Volume:  72     ISSN:  0301-4622     ISO Abbreviation:  Biophys. Chem.     Publication Date:  1998 May 
Date Detail:
Created Date:  1998-07-23     Completed Date:  1998-07-23     Revised Date:  2006-11-15    
Medline Journal Info:
Nlm Unique ID:  0403171     Medline TA:  Biophys Chem     Country:  NETHERLANDS    
Other Details:
Languages:  eng     Pagination:  223-30     Citation Subset:  IM    
Department of Applied Mathematics and Computer Science, Weizmann Institute of Science, Rehovot, Israel.
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MeSH Terms
Autoimmunity / immunology
Immunity / immunology
Immunologic Techniques*
Mathematical Computing
Models, Biological*
T-Lymphocytes / immunology

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