A Practical Guide to Using Glycomics Databases
This book provides glycoscientists with a handbook of useful databases that can be applied to glycoscience research. Although many databases are now publicly available, one of the hurdles for their users is the learning curve required to effectively utilize those databases. Therefore, this book not...
| Συγγραφή απο Οργανισμό/Αρχή: | |
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| Άλλοι συγγραφείς: | |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Tokyo :
Springer Japan : Imprint: Springer,
2017.
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| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- Preface
- Part I Introduction
- Chapter1 Introduction
- Chapter2 Development of Carbohydrate Nomenclature and Representation
- Part II Monosaccharide and glycan structures
- Chapter 3 Translation and validation of carbohydrate residue names with MonosaccharideDB routines
- Chapter4 Using GlyTouCan version 1.0: The first international glycan structure repository
- Chapter5 CARBOHYDRATE STRUCTURE DATABASE (CSDB) – examples of usage
- Part III Glyco-related genes and proteins
- Chapter6 The CAZy Database / The Carbohydrate-Active Enzyme (CAZy) database: principles and usage guidelines
- Chapter7 Glyco3D: A Suite of Inter-linked Databases of 3D Structures of Complex Carbohydrates, Lectins, Antibodies and Glycosyltransferases
- Chapter8 GlycoGene Database (GGDB) on the Semantic Web
- Chapter9 KEGG GLYCAN Database
- Part IV Glycoproteomics data
- Chapter10 Exploring the UniCarbKB Database
- Chapter11 GlycoProtDB –A database of glycoproteins mapped with actual glycosylation sites identified by mass spectrometry
- Part V Glycan interactions
- Chapter12 GlycoEpitope
- Chapter13 SugarBindDB
- Chapter14 PAConto - RDF representation of PACDB data and Ontology of Infectious Diseases known to be related to Glycan Binding
- Part VI Glycan data analysis
- Chapter15 RINGS: a web resource of tools for analyzing glycomics data
- Chapter16 Glycan data retrieval and analysis using GLYCOSCIENCES.de applications
- Chapter17 Glycobiology meets the Semantic Web.
