Bioinformatics for Immunomics / edited by Darren D.R. Flower, Matthew Davies, Shoba Ranganathan.

Springer eBooks

Computational Vaccinology -- The Immuno Polymorphism Database -- The IMGT/HLA Database -- Ontology Development for the Immune Epitope Database -- TEPIDAS: A DAS Server for Integrating T-Cell Epitope Annotations -- Databases and Web-Based Tools for Innate Immunity -- Structural Immunoinformatics: Understanding MHC-Peptide-TR Binding -- Discovery of Conserved Epitopes Through Sequence Variability Analyses -- Tunable Detectors for Artificial Immune Systems: From Model to Algorithm -- Defining the Elusive Molecular Self -- A Bioinformatic Platform for a Bayesian, Multiphased, Multilevel Analysis in Immunogenomics.

The field of Immunomics has developed within the post-genomic era as a response to the massive amount of biological and immunological data now available to researchers. Immunomics crosses the disciplines of immunology, genomics, proteomics and computational biology and address some fundamental problems in biological and medical research. This book covers some of the rich sources of immunological data that are currently available and describes the various bioinformatics techniques that have been utilized to aid our understanding of the immune system. It also describes the nature of the self/non-self distinction that forms the basis of immunological theory and how computational modeling can help to clarify our understanding of how the immune system works.

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