Immunoinformatics : Predicting Immunogenicity In Silico /

Detalles Bibliográficos
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Flower, Darren R. (Editor )
Formato: eBook
Lenguaje:English
Publicado: Totowa, NJ : Humana Press : Imprint: Humana, 2007.
Edición:1st ed. 2007.
Colección:Methods in Molecular Biology, 409
Materias:
Tabla de Contenidos:
  • Databases
  • IMGT®, the International ImmunoGeneTics Information System® for Immunoinformatics
  • The IMGT/HLA Database
  • IPD
  • SYFPEITHI
  • Searching and Mapping of T-Cell Epitopes, MHC Binders, and TAP Binders
  • Searching and Mapping of B-Cell Epitopes in Bcipep Database
  • Searching Haptens, Carrier Proteins, and Anti-Hapten Antibodies
  • Defining HLA Supertypes
  • The Classification of HLA Supertypes by GRID/CPCA and Hierarchical Clustering Methods
  • Structural Basis for HLA-A2 Supertypes
  • Definition of MHC Supertypes Through Clustering of MHC Peptide-Binding Repertoires
  • Grouping of Class I HLA Alleles Using Electrostatic Distribution Maps of the Peptide Binding Grooves
  • Predicting Peptide-MHC Binding
  • Prediction of Peptide-MHC Binding Using Profiles
  • Application of Machine Learning Techniques in Predicting MHC Binders
  • Artificial Intelligence Methods for Predicting T-Cell Epitopes
  • Toward the Prediction of Class I and II Mouse Major Histocompatibility Complex-Peptide-Binding Affinity
  • Predicting the MHC-Peptide Affinity Using Some Interactive-Type Molecular Descriptors and QSAR Models
  • Implementing the Modular MHC Model for Predicting Peptide Binding
  • Support Vector Machine-Based Prediction of MHC-Binding Peptides
  • In Silico Prediction of Peptide-MHC Binding Affinity Using SVRMHC
  • HLA-Peptide Binding Prediction Using Structural and Modeling Principles
  • A Practical Guide to Structure-Based Prediction of MHC-Binding Peptides
  • Static Energy Analysis of MHC Class I and Class II Peptide-Binding Affinity
  • Molecular Dynamics Simulations
  • An Iterative Approach to Class II Predictions
  • Building a Meta-Predictor for MHC Class II-Binding Peptides
  • Nonlinear Predictive Modeling of MHC Class II-Peptide Binding Using Bayesian Neural Networks
  • Predicting other Properties of Immune Systems
  • TAPPred Prediction of TAP-Binding Peptides in Antigens
  • Prediction Methods for B-cell Epitopes
  • HistoCheck
  • Predicting Virulence Factors of Immunological Interest
  • Immunoinformatics and the in Silico Prediction of Immunogenicity
  • Immunoinformatics and the in Silico Prediction of Immunogenicity.