9. Sequence-Based Computational Approaches to Vaccine Discovery and Design

  1. W. John W. Morrow PhD, DSc, FRCPath2,
  2. Nadeem A. Sheikh PhD3,
  3. Clint S. Schmidt PhD4 and
  4. D. Huw Davies PhD5
  1. Darrick Carter PhD

Published Online: 20 JUN 2012

DOI: 10.1002/9781118345313.ch9

Vaccinology: Principles and Practice

Vaccinology: Principles and Practice

How to Cite

Carter, D. (2012) Sequence-Based Computational Approaches to Vaccine Discovery and Design, in Vaccinology: Principles and Practice (eds W. J. W. Morrow, N. A. Sheikh, C. S. Schmidt and D. H. Davies), Wiley-Blackwell, Oxford, UK. doi: 10.1002/9781118345313.ch9

Editor Information

  1. 2

    Seattle, WA, USA

  2. 3

    Dendreon Corporation, Seattle, WA, USA

  3. 4

    NovaDigm Therapeutics, Inc., Grand Forks, ND, USA

  4. 5

    University of California at Irvine, Irvine, CA, USA

Author Information

  1. Protein Advances, Inc., Seattle, WA, and Infectious Disease Research Institute, Seattle, WA, USA

Publication History

  1. Published Online: 20 JUN 2012
  2. Published Print: 3 AUG 2012

ISBN Information

Print ISBN: 9781405185745

Online ISBN: 9781118345313



  • sequence alignment;
  • artificial neural net;
  • epitope prediction;
  • support vector machine;
  • hidden Markov model;
  • position specific scoring matrix;
  • structure-based epitope prediction;
  • backpropagation;
  • machine learning;
  • substitution table


The use of computational approaches in predicting B-cell and MHC class I and II T-cell epitopes as well as in deciding on candidates for vaccination is gaining popularity due to the increased speed and accuracy of these approaches. This chapter gives an overview of various computational techniques used and attempts to give the user the ability to program their own sequence alignment program as well as an artificial neural net based on feedforward and backpropagation learning. These introductions are meant to provide a basis for further exploration and application of these techniques.