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In Silico Immunology

  • Book
  • © 2007

Overview

Editors:
  1. Darren Flower

    1. The Jenner Institute, University of Oxford, UK

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  2. Jon Timmis

    1. University of York, Heslington, UK

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  • In silico Immunology" summarizes the three different disciplines now poised to engineer a paradigm shift from hypothesis- to data-driven research: theoretical immunology, immunoinformatics, and Artificial Immune Systems (AIS)
  • It 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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Table of contents (18 chapters)

  1. Front Matter

    Pages I-XVIII
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  2. Overview of the book

    1. Overview of the book

      Pages 1-8

  3. Introducing In Silico Immunology

    1. Front Matter

      Pages 9-9
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    2. Innate and Adaptive Immunity

      • Adrian Robins
      Pages 11-21

    3. Immunoinformatics and Computational Vaccinology: A Brief Introduction

      • Paul D Taylor, Darren R Flower
      Pages 23-46

    4. A Beginners Guide to Artificial Immune Systems

      • Jon Timmis, Paul Andrews
      Pages 47-62

  4. The Nature of Natural and Artificial Immune Systems

    1. Front Matter

      Pages 63-63
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    2. Computational Models of B cell and T cell Receptors

      • Ha Youn Lee, Alan S. Perelson
      Pages 65-81

    3. Modelling Immunological Memory

      • Simon Garrett, Martin Robbins, Joanne Walker, William Wilson, Uwe Aickelin
      Pages 83-108

    4. Capturing Degeneracy in the Immune System

      • Paolo Tieri, Gastone C. Castellani, Daniel Remondini, Silvana Valensin, Jonathan Loroni, Stefano Salvioli et al.
      Pages 109-118

    5. Alternative Inspiration For Artificial Immune Systems: Exploiting Cohen’s Cognitive Immune Model

      • Paul Andrews, Jon Timmis
      Pages 119-137

    6. Empirical, AI, and QSAR Approaches to Peptide-MHC Binding Prediction

      • Channa K Hattotuwagama, Pingping Guan, Matthew Davies, Debra J Taylor, Valerie Walshe, Shelley L Hemsley et al.
      Pages 139-175

    7. MHC diversity in Individuals and Populations

      • José A. M. Borghans, Can KeÅŸmir, Rob J. De Boer
      Pages 177-195

    8. Identifying Major Histocompatibility Complex Supertypes

      • Pingping Guan, Irini A. Doytchinova, Darren R. Flower
      Pages 197-233

    9. Biomolecular Structure Prediction Using Immune Inspired Algorithms

      • Vincenzo Cutello, Giuseppe Nicosia
      Pages 235-261

  5. How Natural and Artificial Immune Systems Interact with the World

    1. Front Matter

      Pages 263-263
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    2. Embodiment

      • Susan Stepney
      Pages 265-288

    3. The Multi-scale Immune Response to Pathogens: M. tuberculosis as an Example

      • Denise Kirschner
      Pages 289-311

    4. Go Dutch: Exploit Interactions and Environments with Artificial Immune Systems

      • Mark Neal, B. C. Trapnell Jr.
      Pages 313-330

    5. Immune Inspired Learning in a Distributed Environment

      • Andrew Watkins
      Pages 331-350
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Keywords

About this book

Whatever its final readership and impact, we, the Editors, feel this book is im­ portant. It addresses the realisation that there is a deep and abiding synergy, albeit one only now being properly explored and exploited, between immunol­ ogy and computational science. This area of intersection we christen in silico immunology. Immunology is an inspiration for computational scientists seek­ ing practical and philosophical metaphors for their work; but, at the same time, it is itself a biological discipline of such discombobulating complexity that only computational help as different as simulation and data warehousing can make its modern study tractable. Thus immunology both inspires but also requires computational science. This book deals in detail with the three main areas of in silico immunology: theoretical immunology, immunoinformatics, and artificial immune systems. While all of these are now well-established the interactions between the three are only beginning to be developed. It is a truly exciting time to be working in in silicio immunology. We are reaching a critical mass that will enable great strides to be taken and significant achievements to be made. Like David Hume, we may yet come to regret that this book falls still born from the press but we hope not. Hopefully it will instead strike a cord and tap into a burgeoning Zeitgeist ready to capitalise on the remarkable potential that is in silico immunology.

Editors and Affiliations

  • The Jenner Institute, University of Oxford, UK

    Darren Flower

  • University of York, Heslington, UK

    Jon Timmis

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