Description |
1 online resource (xv, 438 pages) : illustrations (some color) |
Series |
Methods in molecular biology ; 409 |
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Methods in molecular biology (Clifton, N.J.) ; v. 409
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Contents |
Immunoinformatics and the in silico prediction of immunogenicity. An introduction / D.R. Flower -- IMGT, the international immunogenetics information system for immunoinformatics. Methods for querying IMGT databases, tools, and web resources in the context of immunoinformatics / M.P. Lefranc -- The IMGT/HLA database / J. Robinson and S.G. Marsh -- IPD: The immuno polymorphism database / J. Robinson and S.G. Marsh -- SYFPEITHI: Database for searching and T-cell epitope prediction / M.M. Schuler, M.D. Nastke and S. Stevanovikc -- Searching and mapping of T-cell epitopes, MHC binders, and tap binders / M. Bhasin, S. Lata and G.P. Raghava -- Searching and mapping of B-cell epitopes in bcipep database / S. Saha and G.P. Raghava -- Searching haptens, carrier proteins, and anti-hapten antibodies / S. Srivastava [and others] -- The classification of HLA supertypes by grid/cpca and hierarchical clustering methods / P. Guan, I.A. Doytchinova and D.R. Flower -- Structural basis for HLA-A2 supertypes / P. Kangueane and M.K. Sakharkar -- Definition of MHC supertypes through clustering of MHC peptide-binding repertoires / P.A. Reche and E.L. Reinherz -- Grouping of class I HLA alleles using electrostatic distribution maps of the peptide binding grooves / P. Kangueane and M.K. Sakharkar -- Prediction of peptide-MHC binding using profiles / P.A. Reche and E.L. Reinherz -- Application of machine learning techniques in predicting MHC binders / S. Lata, M. Bhasin and G.P. Raghava -- Artificial intelligence methods for predicting T-cell epitopes / Y. Zhao, M.H. Sung and R. Simon -- 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 / C.K. Hattotuwagama, I.A. Doytchinova and D.R. Flower -- Predicting the MHC-peptide affinity using some interactive-type molecular descriptors and QSAR models / T.H. Lin -- Implementing the modular MHC model for predicting peptide binding / D.S. DeLuca and R. Blasczyk -- Support vector machine-based prediction of MHC-binding peptides / P. Donnes -- In silico prediction of peptide-MHC binding affinity using SVRMHC / W. Liu [and others] -- HLA-peptide binding prediction using structural and modeling principles / P. Kangueane and M.K. Sakharkar -- A practical guide to structure-based prediction of MHC-binding peptides / S. Ranganathan and J.C. Tong -- Static energy analysis of MHC class I and class II peptide-binding affinity / M.N. Davies and D.R. Flower -- Molecular dynamics simulations: Bring biomolecular structures alive on a computer / S. Wan, P.V. Coveney and D.R. Flower -- An iterative approach to class II predictions / R.R. Mallios -- Building a meta-predictor for MHC class II-binding peptides / L. Huang [and others] -- Nonlinear predictive modeling of MHC class II-peptide binding using bayesian neural networks / D.A. Winkler and F.R. Burden -- TAPPred prediction of TAP-binding peptides in antigens / M. Bhasin, S. Lata and G.P. Raghava -- Prediction methods for B-cell epitopes / S. Saha and G.P. Raghava -- Histocheck. Evaluating structural and functional MHC similarities / D.S. DeLuca and R. Blasczyk -- Predicting virulence factors of immunological interest / S. Saha and G.P. Raghava -- Immunoinformatics. Predicting immunogenicity in silico. Preface / D.R. Flower |
Summary |
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 |
Analysis |
immunologie |
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immunology |
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informatica |
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informatics |
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Genome informatics |
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Genoominformatica |
Bibliography |
Includes bibliographical references and index |
Notes |
English |
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Print version record |
Subject |
Immunoinformatics.
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Immunology -- Computer simulation
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Immunological tolerance -- Computer simulation
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Immune system.
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Mathematical models.
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Medical informatics.
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Medicine -- Data processing.
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Immunogenetics.
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Methodology.
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Bioinformatics.
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Computational biology.
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Biology.
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Biological models.
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Life sciences.
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Anatomy.
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Medical personnel.
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Physical sciences.
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Computational Biology -- methods
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Immune System
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Models, Immunological
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Models, Theoretical
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Allergy and Immunology
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Medical Informatics
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Immunogenetics
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Databases, Factual
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Methods
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Computational Biology
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Biology
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Databases as Topic
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Investigative Techniques
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Genetics
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Information Science
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Medicine
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Hemic and Immune Systems
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Models, Biological
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Informatics
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Analytical, Diagnostic and Therapeutic Techniques and Equipment
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Biological Science Disciplines
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Anatomy
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Information Storage and Retrieval
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Health Occupations
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Natural Science Disciplines
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Disciplines and Occupations
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Immune System Phenomena
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Medical Informatics Applications
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Animal Structures
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Health Personnel
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Health Workforce
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mathematical models.
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methodology.
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biology.
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biological sciences.
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anatomy.
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physical sciences.
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SCIENCE -- Life Sciences -- Anatomy & Physiology.
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Immunological tolerance -- Computer simulation.
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Allergy and Immunology.
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Computational Biology -- methods.
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Medical Informatics -- methods.
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Immunogenetics -- methods.
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Databases, Factual.
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Immunoinformatics.
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Immunology -- Computer simulation.
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Physical sciences
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Methodology
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Medicine -- Data processing
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Medical personnel
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Medical informatics
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Mathematical models
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Life sciences
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Immunogenetics
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Immune system
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Computational biology
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Biology
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Biological models
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Bioinformatics
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Anatomy
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Immunoinformatics
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Immunology -- Computer simulation
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Genre/Form |
Laboratory manuals.
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Manuels de laboratoire.
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Form |
Electronic book
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Author |
Flower, Darren R.
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ISBN |
9781603271189 |
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160327118X |
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1280945257 |
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9781280945250 |
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661094525X |
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9786610945252 |
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