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Bioinformatics for Immunomics (Hardcover, 2010 ed.): Darren D. R. Flower, Matthew Davies, Shoba Ranganathan Bioinformatics for Immunomics (Hardcover, 2010 ed.)
Darren D. R. Flower, Matthew Davies, Shoba Ranganathan
R5,455 Discovery Miles 54 550 Ships in 10 - 15 working days

Like many words, the term "immunomics" equates to different ideas contingent on context. For a brief span, immunomics meant the study of the Immunome, of which there were, in turn, several different definitions. A now largely defunct meaning rendered the Immunome as the set of antigenic peptides or immunogenic proteins within a single microorganism - be that virus, bacteria, fungus, or parasite - or microbial population, or antigenic or allergenic proteins and peptides derived from the environment as a whole, containing also proteins from eukaryotic sources. However, times have changed and the meaning of immunomics has also changed. Other newer definitions of the Immunome have come to focus on the plethora of immunological receptors and accessory molecules that comprise the host immune arsenal. Today, Immunomics or immunogenomics is now most often used as a synonym for high-throughput genome-based immunology. This is the study of aspects of the immune system using high-throughput techniques within a conc- tual landscape borne of both clinical and biophysical thinking.

Bioinformatics for Immunomics (Paperback, 2010 ed.): Darren D. R. Flower, Matthew Davies, Shoba Ranganathan Bioinformatics for Immunomics (Paperback, 2010 ed.)
Darren D. R. Flower, Matthew Davies, Shoba Ranganathan
R5,402 Discovery Miles 54 020 Ships in 10 - 15 working days

Like many words, the term "immunomics" equates to different ideas contingent on context. For a brief span, immunomics meant the study of the Immunome, of which there were, in turn, several different definitions. A now largely defunct meaning rendered the Immunome as the set of antigenic peptides or immunogenic proteins within a single microorganism - be that virus, bacteria, fungus, or parasite - or microbial population, or antigenic or allergenic proteins and peptides derived from the environment as a whole, containing also proteins from eukaryotic sources. However, times have changed and the meaning of immunomics has also changed. Other newer definitions of the Immunome have come to focus on the plethora of immunological receptors and accessory molecules that comprise the host immune arsenal. Today, Immunomics or immunogenomics is now most often used as a synonym for high-throughput genome-based immunology. This is the study of aspects of the immune system using high-throughput techniques within a conc- tual landscape borne of both clinical and biophysical thinking.

In Silico Immunology (Paperback, Softcover reprint of hardcover 1st ed. 2007): Darren D. R. Flower, Jon Timmis In Silico Immunology (Paperback, Softcover reprint of hardcover 1st ed. 2007)
Darren D. R. Flower, Jon Timmis
R4,279 Discovery Miles 42 790 Ships in 10 - 15 working days

This book outlines three emergent disciplines, which are now poised to engineer a paradigm shift from hypothesis- to data-driven research: theoretical immunology, immunoinformatics, and Artificial Immune Systems. It details how these disciplines will enable new understanding to emerge from the analysis of complex datasets. Coverage shows how these three are set to transform immunological science and the future of health care.

In Silico Immunology (Hardcover, 2007 ed.): Darren D. R. Flower, Jon Timmis In Silico Immunology (Hardcover, 2007 ed.)
Darren D. R. Flower, Jon Timmis
R4,930 R4,362 Discovery Miles 43 620 Save R568 (12%) Ships in 12 - 17 working days

Theoretical immunology is the application of mathematical modeling to diverse aspects of immunology. Immuno informatics, the application of computational informatics to the study of immunological macromolecules, addresses questions in immunobiology and vaccinology, as well as addressing issues of data management, and can design and implement new experimental strategies. Artificial Immune Systems (AIS) uses ideas and concepts from immunology to guide and inspire new algorithms, data structures, and software development. These three different disciplines are now poised to engineer a paradigm shift from hypothesis- to data-driven research, with new understanding emerging from the analysis of complex datasets: theoretical immunology, immunoinformatics, and Artificial Immune Systems (AIS). In Silico Immunology will summarize these emergent disciplines and will address the issue of synergy as it shows how these three are set to transform immunological science and the future of health care.

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