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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.
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.
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.
.".". this book was written from start to finish by one extremely dedicated and erudite individual. The author has done an excellent job of covering the many topics that fall under the umbrella of computational biology for vaccine design, demonstrating an admirable command of subject matter in fields as disparate as object-oriented databases and regulation of T cell response. Simply put, it has just the right breadth and depth, and it reads well. In fact, readability is one of its virtues--making the book enticing and useful, all at once..."" Human Vaccines, 2010 .".". This book has several strong points. Although there are many textbooks that deal with vaccinology, few attempts have been made to bring together descriptions of vaccines in history, basic bioinformatics, various computational solutions and challenges in vaccinology, detailed experimental methodologies, and cutting-edge technologies... This book may well serve as a first line of reference for all biologists and computer scientists..."" -Virology Journal, 2009
Vaccinology now has at its disposal an array of post-genomic approaches of great power. None has a more persuasive potential impact than the application of computational informatics to vaccine discovery; the recent expansion in genome data and the parallel increase in cheap computing power have placed the bioinformatics exploration of pathogen genomes centre stage for vaccine researchers. This is the first book to address the area of bioinformatics as applied to rational vaccine design, discussing the ways in which bioinformatics can contribute to improved vaccine development byintroducing the subject of harnessing the mathematical and computing power inherent in bioinformatics to the study of vaccinologyputting it into a historical and societal context, and exploring the scope of its methods and applications. "Bioinformatics for Vaccinology" is a one-stop introduction to computational vaccinology. It will be of particular interest to bioinformaticians with an interest in immunology, as well as to immunologists, and other biologists who need to understand how advances in theoretical and computational immunobiology can transform their working practices.
IAU Symposium 103 was held at University College London, August 9-13 1982. This volume contains the proceedings of the meetin- invited papers, abstracts of contributed papers, and discussion. As is nON custanary with the proceedings of IAU Symposia, the manuscript was canpiled fran camera-ready copy. The Editor was responsible for the preparation of the abstracts of the contributed papers and the discussion, the authors of the invited papers for the preparation of their 0Nn reviews. The discussion at the meeting was lively and infonnative, and the Editor hopes that a reasonably faithful and readable record of the discussion is to be found in these proceedings. In accordance with the wish of the Scientific Organising Committee, an object index has been canpiled and appended. It is to be hoped that the index will augment the usefulness of the volune. The Editor is greatly indebted to M. J. Barlow for his help in preparing the index. Financial assistance for the meeting was provided by the IAU and University College London. The hospitality received during the excursion to the Old Royal Observatory and National Maritime MUseum, Greenwich, is gratefully acknowledged. The task of editing these proceedings has been greatly facilitated by the excellent secretarial assistance of V. A. Kerr. David Flower Durham, October 1982 xiii D. R. Flower (ed.), Planetary Nebulae, xiii.
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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