In Silico Immunology

  • Darren Flower
  • Jon Timmis

Table of contents

  1. Front Matter
    Pages I-XVIII
  2. Overview of the book

  3. Introducing In Silico Immunology

    1. Front Matter
      Pages 9-9
    2. Adrian Robins
      Pages 11-21
    3. Jon Timmis, Paul Andrews
      Pages 47-62
  4. The Nature of Natural and Artificial Immune Systems

    1. Front Matter
      Pages 63-63
    2. Ha Youn Lee, Alan S. Perelson
      Pages 65-81
    3. Simon Garrett, Martin Robbins, Joanne Walker, William Wilson, Uwe Aickelin
      Pages 83-108
    4. Paolo Tieri, Gastone C. Castellani, Daniel Remondini, Silvana Valensin, Jonathan Loroni, Stefano Salvioli et al.
      Pages 109-118
    5. Channa K Hattotuwagama, Pingping Guan, Matthew Davies, Debra J Taylor, Valerie Walshe, Shelley L Hemsley et al.
      Pages 139-175
    6. José A. M. Borghans, Can Keşmir, Rob J. De Boer
      Pages 177-195
    7. Pingping Guan, Irini A. Doytchinova, Darren R. Flower
      Pages 197-233
    8. Vincenzo Cutello, Giuseppe Nicosia
      Pages 235-261
  5. How Natural and Artificial Immune Systems Interact with the World

    1. Front Matter
      Pages 263-263
    2. Susan Stepney
      Pages 265-288

About this book

Introduction

Immunology is an all important science, addressing, as it does the most pressing medical needs of our time: infectious disease and transplantation medicine. It has given us vaccines on the one hand and therapeutic antibodies on the other. After a century of empirical research, it is now poised to finally reinvent itself as a quantitative, genome-based science. Like most biological disciplines, immunology must capitalize on the potentially overwhelming deluge of new data delivered by post-genomic, high throughput technologies; data which is both bewilderingly complex and delivered on a hitherto unimaginable scale.

Theoretical immunology is the application of mathematical modeling to diverse aspects of immunology ranging from T cell selection in the Thymus to the epidemiology of vaccination. Immunoinformatics, the application of computational informatics to the study of immunological macromolecules, addresses important questions in immunobiology and vaccinology. Immunoinformatics, addresses issues of data management, and has the ability to design and implement efficient new experimental strategies. Artificial Immune Systems (AIS) is an area of computer science which uses ideas and concepts from immunology to guide and inspire new algorithms, data structures, and software development. The influence of AIS is now becoming highly synergistic through its interaction with immunoinformatics.

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" is a book for the future: it will summarize these emergent disciplines and, while focusing on cutting edge developments, will address the issue of synergy as it shows how these three are set to transform immunological science and the future of health care.

Keywords

In silico Master Patient Index algorithms artificial immune systems computational science immunoinformatics immunology theoretical immunology

Editors and affiliations

  • Darren Flower
    • 1
  • Jon Timmis
    • 2
  1. 1.The Jenner InstituteUniversity of OxfordUK
  2. 2.University of YorkHeslingtonUK

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-39241-7
  • Copyright Information Springer Science+Business Media, LLC 2007
  • Publisher Name Springer, Boston, MA
  • eBook Packages Biomedical and Life Sciences
  • Print ISBN 978-0-387-39238-7
  • Online ISBN 978-0-387-39241-7
  • About this book