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Immunoinformatics

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Cover of 'Immunoinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 Immunoinformatics and the in Silico Prediction of Immunogenicity
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    Chapter 2 IMGT ® , the International ImmunoGeneTics Information System ® for Immunoinformatics
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    Chapter 3 The IMGT/HLA Database
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    Chapter 4 IPD
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    Chapter 5 SYFPEITHI
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    Chapter 6 Searching and Mapping of T-Cell Epitopes, MHC Binders, and TAP Binders
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    Chapter 7 Searching and Mapping of B-Cell Epitopes in Bcipep Database
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    Chapter 8 Searching Haptens, Carrier Proteins, and Anti-Hapten Antibodies
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    Chapter 9 The Classification of HLA Supertypes by GRID/CPCA and Hierarchical Clustering Methods
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    Chapter 10 Structural Basis for HLA-A2 Supertypes
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    Chapter 11 Definition of MHC Supertypes Through Clustering of MHC Peptide-Binding Repertoires
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    Chapter 12 Grouping of Class I HLA Alleles Using Electrostatic Distribution Maps of the Peptide Binding Grooves
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    Chapter 13 Prediction of Peptide-MHC Binding Using Profiles
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    Chapter 14 Application of Machine Learning Techniques in Predicting MHC Binders
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    Chapter 15 Artificial Intelligence Methods for Predicting T-Cell Epitopes
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    Chapter 16 Toward the Prediction of Class I and II Mouse Major Histocompatibility Complex-Peptide-Binding Affinity
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    Chapter 17 Predicting the MHC-Peptide Affinity Using Some Interactive-Type Molecular Descriptors and QSAR Models
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    Chapter 18 Implementing the Modular MHC Model for Predicting Peptide Binding
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    Chapter 19 Support Vector Machine-Based Prediction of MHC-Binding Peptides
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    Chapter 20 In Silico Prediction of Peptide-MHC Binding Affinity Using SVRMHC
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    Chapter 21 HLA-Peptide Binding Prediction Using Structural and Modeling Principles
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    Chapter 22 A practical guide to structure-based prediction of MHC-binding peptides.
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    Chapter 23 Static Energy Analysis of MHC Class I and Class II Peptide-Binding Affinity
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    Chapter 24 Molecular Dynamics Simulations
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    Chapter 25 An Iterative Approach to Class II Predictions
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    Chapter 26 Building a Meta-Predictor for MHC Class II-Binding Peptides
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    Chapter 27 Nonlinear Predictive Modeling of MHC Class II-Peptide Binding Using Bayesian Neural Networks
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    Chapter 28 TAPPred Prediction of TAP-Binding Peptides in Antigens
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    Chapter 29 Prediction Methods for B-cell Epitopes
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    Chapter 30 HistoCheck
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    Chapter 31 Predicting Virulence Factors of Immunological Interest
Attention for Chapter 12: Grouping of Class I HLA Alleles Using Electrostatic Distribution Maps of the Peptide Binding Grooves
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Citations

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Chapter title
Grouping of Class I HLA Alleles Using Electrostatic Distribution Maps of the Peptide Binding Grooves
Chapter number 12
Book title
Immunoinformatics
Published by
Humana Press, January 2007
DOI 10.1007/978-1-60327-118-9_12
Book ISBNs
978-1-58829-699-3, 978-1-60327-118-9
Authors

Pandjassarame Kangueane, Meena Kishore Sakharkar, Kangueane, Pandjassarame, Sakharkar, Meena Kishore

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 11%
Unknown 8 89%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 22%
Lecturer > Senior Lecturer 1 11%
Student > Bachelor 1 11%
Professor 1 11%
Student > Master 1 11%
Other 2 22%
Unknown 1 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 78%
Immunology and Microbiology 1 11%
Unknown 1 11%