In Silico Immunology

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.