Immunoinformatics: Predicting Immunogenicity In Silico
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 im...
Gespeichert in:
| Weitere Verfasser: | |
|---|---|
| Format: | Elektronisch E-Book |
| Sprache: | English |
| Veröffentlicht: |
Totowa, NJ
Humana Press
2007
|
| Schriftenreihe: | Methods in Molecular Biology™
409 |
| Schlagworte: | |
| Online-Zugang: | UBR01 TUM01 Volltext |
| Zusammenfassung: | 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 |
| Beschreibung: | 1 Online-Ressource (XV, 438 p. 111 illus., 5 illus. in color) |
| ISBN: | 9781603271189 |
| DOI: | 10.1007/978-1-60327-118-9 |
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| 520 | |a 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 | ||
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| id | DE-604.BV044950634 |
| illustrated | Not Illustrated |
| indexdate | 2024-07-10T08:05:34Z |
| institution | BVB |
| isbn | 9781603271189 |
| language | English |
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| physical | 1 Online-Ressource (XV, 438 p. 111 illus., 5 illus. in color) |
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| spelling | Immunoinformatics Predicting Immunogenicity In Silico edited by Darren R. Flower Totowa, NJ Humana Press 2007 1 Online-Ressource (XV, 438 p. 111 illus., 5 illus. in color) txt rdacontent c rdamedia cr rdacarrier Methods in Molecular Biology™ 409 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 Life Sciences Bioinformatics Life Sciences, general Theory of Computation Immunology Human Genetics Cell Biology Life sciences Human genetics Computers Cell biology Flower, Darren R. edt Erscheint auch als Druck-Ausgabe 9781588296993 https://doi.org/10.1007/978-1-60327-118-9 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Immunoinformatics Predicting Immunogenicity In Silico Life Sciences Bioinformatics Life Sciences, general Theory of Computation Immunology Human Genetics Cell Biology Life sciences Human genetics Computers Cell biology |
| title | Immunoinformatics Predicting Immunogenicity In Silico |
| title_auth | Immunoinformatics Predicting Immunogenicity In Silico |
| title_exact_search | Immunoinformatics Predicting Immunogenicity In Silico |
| title_full | Immunoinformatics Predicting Immunogenicity In Silico edited by Darren R. Flower |
| title_fullStr | Immunoinformatics Predicting Immunogenicity In Silico edited by Darren R. Flower |
| title_full_unstemmed | Immunoinformatics Predicting Immunogenicity In Silico edited by Darren R. Flower |
| title_short | Immunoinformatics |
| title_sort | immunoinformatics predicting immunogenicity in silico |
| title_sub | Predicting Immunogenicity In Silico |
| topic | Life Sciences Bioinformatics Life Sciences, general Theory of Computation Immunology Human Genetics Cell Biology Life sciences Human genetics Computers Cell biology |
| topic_facet | Life Sciences Bioinformatics Life Sciences, general Theory of Computation Immunology Human Genetics Cell Biology Life sciences Human genetics Computers Cell biology |
| url | https://doi.org/10.1007/978-1-60327-118-9 |
| work_keys_str_mv | AT flowerdarrenr immunoinformaticspredictingimmunogenicityinsilico |