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In Silico Immunology

Erschienen am 04.11.2010, 1. Auflage 2007
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Bibliografische Daten
ISBN/EAN: 9781441942647
Sprache: Englisch
Umfang: xviii, 451 S., 89 s/w Illustr., 451 p. 89 illus.
Einband: kartoniertes Buch

Beschreibung

InhaltsangabePreface.- List of Contributors.- Overview.- Innate and Adaptive Immunity.- Part I Introducing In Silico Immunology: Immunoinformatics and Computational Vaccinology: A Brief Introduction.- A Beginners Guide to Artificial Immune Systems.- Part II The Nature of Natural and Artificial Immune Systems: Computational Models of B Cell and T Cell Receptors.- Modelling Immunological Memory.- Capturing Degeneracy in the Immune System.- Alternative Inspiration for Artificial Immune Systems: Exploiting Cohen's Cognitive Immune Model.- Empirical, AI, and QSAR Approaches to Peptide-MHC Binding Prediction.- MHC Diversity in Individuals and Populations.- Identifying Major Histocompatibility Complex Supertypes.- Biomolecular Structure Prediction Using Immune Inspired Algorithms.- Part III How Natural and Artificial Immune Systems Interact with the World: Embodiment.- The Multi-Scale Immune Response to Pathogens: M. Tuberculosis as an Example.- Go Dutch: Exploit Interactions and Environments with Artificial Immune Systems.- Immune Inspired Learning in a Distributed Environment.- Mathematical Analysis of AIS Dynamics and Performance.- Conceptualizing the Self-Nonself Discrimination by the Vertebrate Immune System.- References.- Index.

Inhalt

Preface.- List of Contributors.- Overview.- Innate and Adaptive Immunity.- Part I Introducing In Silico Immunology: Immunoinformatics and Computational Vaccinology: A Brief Introduction.- A Beginners Guide to Artificial Immune Systems.- Part II The Nature of Natural and Artificial Immune Systems: Computational Models of B Cell and T Cell Receptors.- Modelling Immunological Memory.- Capturing Degeneracy in the Immune System.- Alternative Inspiration for Artificial Immune Systems: Exploiting Cohen¿s Cognitive Immune Model.- Empirical, AI, and QSAR Approaches to Peptide-MHC Binding Prediction.- MHC Diversity in Individuals and Populations.- Identifying Major Histocompatibility Complex Supertypes.- Biomolecular Structure Prediction Using Immune Inspired Algorithms.- Part III How Natural and Artificial Immune Systems Interact with the World: Embodiment.- The Multi-Scale Immune Response to Pathogens: M. Tuberculosis as an Example.- Go Dutch: Exploit Interactions and Environments with Artificial Immune Systems.- Immune Inspired Learning in a Distributed Environment.- Mathematical Analysis of AIS Dynamics and Performance.- Conceptualizing the Self-Nonself Discrimination by the Vertebrate Immune System.- References.- Index.