Immunoinformatics: Predicting Immunogenicity in Silico Book

Preface     v
Contributors     xi
Color Plates     xv
Immunoinformatics and the In Silico Prediction of Immunogenicity: An Introduction   Darren R. Flower     1
Databases
IMGT, the International ImmunoGeneTics Information System for Immunoinformatics: Methods for Querying IMGT Databases, Tools, and Web Resources in the Context of Immunoinformatics   Marie-Paule Lefranc     19
The IMGT/HLA Database   James Robinson   Steven G. E. Marsh     43
IPD: The Immuno Polymorphism Database   James Robinson   Steven G. E. Marsh     61
SYFPEITHI: Database for Searching and T-Cell Epitope Prediction   Mathias M. Schuler   Maria-Dorothea Nastke   Stefan Stevanovic     75
Searching and Mapping of T-Cell Epitopes, MHC Binders, and TAP Binders   Manoj Bhasin   Sneh Lata   Gajendra P. S. Raghava     95
Searching and Mapping of B-Cell Epitopes in Bcipep Database   Sudipto Saha   Gajendra P. S. Raghava     113
Searching Haptens, Carrier Proteins, and Anti-Hapten Antibodies   Shilpy Srivastava   Mahender Kumar Singh   Gajendra P. S. Raghava   Grish C. Varshney     125
Defining HLA Supertypes
The Classification of HLA Supertypes byGRID/CPCA and Hierarchical Clustering Methods   Pingping Guan   Irini A. Doytchinova   Darren R. Flower     143
Structural Basis for HLA-A2 Supertypes   Pandjassarame Kangueane   Meena Kishore Sakharkar     155
Definition of MHC Supertypes Through Clustering of MHC Peptide-Binding Repertoires   Pedro A. Reche   Ellis L. Reinherz     163
Grouping of Class I HLA Alleles Using Electrostatic Distribution Maps of the Peptide Binding Grooves   Pandjassarame Kangueane   Meena Kishore Sakharkar     175
Predicting Peptide-MHC Binding
Prediction of Peptide-MHC Binding Using Profiles   Pedro A. Reche   Ellis L. Reinherz     185
Application of Machine Learning Techniques in Predicting MHC Binders   Sneh Lata   Manoj Bhasin   Gajendra P. S. Raghava     201
Artificial Intelligence Methods for Predicting T-Cell Epitopes   Yingdong Zhao   Myong-Hee Sung   Richard Simon     217
Toward the Prediction of Class I and II Mouse Major Histocompatibility Complex-Peptide-Binding Affinity: In Silico Bioinformatic Step-by-Step Guide Using Quantitative Structure-Activity Relationships   Channa K. Hattotuwagama   Irini A. Doytchinova   Darren R. Flower     227
Predicting the MHC-Peptide Affinity Using Some Interactive-Type Molecular Descriptors and QSAR Models   Thy-Hou Lin     247
Implementing the Modular MHC Model for Predicting Peptide Binding   David S. DeLuca   Rainer Blasczyk     261
Support Vector Machine-Based Prediction of MHC-Binding Peptides   Pierre Donnes     273
In Silico Prediction of Peptide-MHC Binding Affinity Using SVRMHC   Wen Liu   Ji Wan   Xiangshan Meng   Darren R. Flower   Tongbin Li     283
HLA-Peptide Binding Prediction Using Structural and Modeling Principles   Pandjassarame Kangueane   Meena Kishore Sakharkar     293
A Practical Guide to Structure-Based Prediction of MHC-Binding Peptides   Shoba Ranganathan   Joo Chuan Tong     301
Static Energy Analysis of MHC Class I and Class II Peptide-Binding Affinity   Matthew N. Davies   Darren R. Flower     309
Molecular Dynamics Simulations: Bring Biomolecular Structures Alive on a Computer   Shunzhou Wan   Peter V. Coveney   Darren R. Flower     321
An Iterative Approach to Class II Predictions   Ronna Reuben Mallios     341
Building a Meta-Predictor for MHC Class II-Binding Peptides   Lei Huang   Oleksiy Karpenko   Naveen Murugan   Yang Dai     355
Nonlinear Predictive Modeling of MHC Class II-Peptide Binding Using Bayesian Neural Networks   David A. Winkler   Frank R. Burden     365
Predicting other Properties of Immune Systems
TAPPred Prediction of TAP-Binding Peptides in Antigens   Manoj Bhasin   Sneh Lata   Gajendra P. S. Raghava     381
Prediction Methods for B-cell Epitopes   Sudipto Saha   Gajendra P. S. Raghava     387
HistoCheck   David S. DeLuca   Rainer Blasczyk     395
Predicting Virulence Factors of Immunological Interest   Sudipto Saha   Gajendra P. S. Raghava     407
Index     417