Immunoinformatics: Predicting Immunogenicity in Silico

Front Cover
Darren R. Flower
Springer Science & Business Media, Jan 1, 2007 - Allergy and Immunology - 438 pages
0 Reviews
Immunoinformatics: Predicting Immunogenicity In Silico is a primer for researchers interested in this emerging and exciting technology and provides examples in the major areas within the field of immunoinformatics. This volume both engages the reader and provides a sound foundation for the use of immunoinformatics techniques in immunology and vaccinology. The volume is conveniently divided into four sections. The first section, Databases, details various immunoinformatic databases, including IMGT/HLA, IPD, and SYEPEITHI. In the second section, Defining HLA Supertypes, authors discuss supertypes of GRID/CPCA and hierarchical clustering methods, Hla-Ad supertypes, MHC supertypes, and Class I Hla Alleles. The third section, Predicting Peptide-MCH Binding, includes discussions of MCH binders, T-Cell epitopes, Class I and II Mouse Major Histocompatibility, and HLA-peptide binding. Within the fourth section, Predicting Other Properties of Immune Systems, investigators outline TAP binding, B-cell epitopes, MHC similarities, and predicting virulence factors of immunological interest. Immunoinformatics: Predicting Immunogenicity In Silico merges skill sets of the lab-based and the computer-based science professional into one easy-to-use, insightful volume.
 

What people are saying - Write a review

We haven't found any reviews in the usual places.

Contents

I
1
II
19
III
43
IV
61
V
75
VI
95
VII
113
VIII
125
XVIII
247
XIX
261
XX
273
XXI
283
XXII
293
XXIII
301
XXIV
309
XXV
321

IX
142
X
143
XI
155
XII
163
XIII
175
XIV
185
XV
201
XVI
217
XVII
227
XXVI
341
XXVII
355
XXVIII
365
XXIX
381
XXX
387
XXXI
395
XXXII
407
XXXIII
417
Copyright

Other editions - View all

Common terms and phrases

Bibliographic information