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these analyses it became clear that the MHC class I molecule com prised a distinct groove on the external side of the molecule. The sides of the groove are formed by the a-helical structures of the a and a 1 2 domains and a floor which is formed by 8 anti-parallel 13 strands. The various polymorphic residues, as determined from DNA sequence analysis, are localized within these a-helices and 13-plated sheets within the groove. More importantly, these analyses also revealed the presence of elec tron-dense material in the groove. This material was subsequently iden 568 10 tified as a linear peptide of 8-10 amino acids long. • •- High resolu tion crystallographic analyses of the class I MHC structure have revealed the existence of so-called pockets within the grooves of the MHC class I molecules. These pockets designated A-F, exhibited allele-specificity and are directly involved in the binding of the peptide, primarily through interaction with the dominant anchor residues as found in MHC class I associated pep tides. 6,7,9,11 The class II MHC antigens consist on the cell surface of a 34 kD a chain non-covalently associated with a 28 kD 13 chain. With the excep tion of the DR a-chain, all other MHC class II a and 13 chains are poly morphic.
The rapid development of new methods for immunological data collection – from multicolor flow cytometry, through single-cell imaging, to deep sequencing – presents us now, for the first time, with the ability to analyze and compare large amounts of immunological data in health, aging and disease. The exponential growth of these datasets, however, challenges the theoretical immunology community to develop methods for data organization and analysis. Furthermore, the need to test hypotheses regarding immune function, and generate predictions regarding the outcomes of medical interventions, necessitates the development of mathematical and computational models covering processes on multiple scales, from the genetic and molecular to the cellular and system scales. The last few decades have seen the development of methods for presentation and analysis of clonal repertoires (those of T and B lymphocytes) and phenotypic (surface-marker based) repertoires of all lymphocyte types, and for modeling the intricate network of molecular and cellular interactions within the immune systems. This e-Book, which has first appeared as a ‘Frontiers in Immunology’ research topic, provides a comprehensive, online, open access snapshot of the current state of the art on immune system modeling and analysis.
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Animal models of some autoimmune diseases have indicated restricted T-cell receptor use and have suggested therapies based on those data. Patients with naturally occurring diseases have not shown a consistent picture of receptor utilisation. This volume discusses the spectrum of T-cell receptor use in human disease, the relationship between the human and animal findings, and the biological and therapeutic implications of the former.
As a generalization of simple correspondence analysis, multiple correspondence analysis (MCA) is a powerful technique for handling larger, more complex datasets, including the high-dimensional categorical data often encountered in the social sciences, marketing, health economics, and biomedical research. Until now, however, the literature on the su