9. Sequence-Based Computational Approaches to Vaccine Discovery and Design
- W. John W. Morrow PhD, DSc, FRCPath2,
- Nadeem A. Sheikh PhD3,
- Clint S. Schmidt PhD4,
- D. Huw Davies PhD5
Published Online: 20 JUN 2012
DOI: 10.1002/9781118345313.ch9
Copyright © 2012 Blackwell Publishing Ltd
Book Title
Vaccinology: Principles and Practice
Additional Information
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
- 2
Seattle, WA, USA
- 3
Dendreon Corporation, Seattle, WA, USA
- 4
NovaDigm Therapeutics, Inc., Grand Forks, ND, USA
- 5
University of California at Irvine, Irvine, CA, USA
Publication History
- Published Online: 20 JUN 2012
- Published Print: 3 AUG 2012
ISBN Information
Print ISBN: 9781405185745
Online ISBN: 9781118345313
- Summary
- Chapter
- References
Keywords:
- 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
Summary
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.