UniCarbKB: building a knowledge platform for
glycoproteomics
Matthew P. Campbell1
, Robyn Peterson1
, Julien Mariethoz2
, Elisabeth Gasteiger3
,
Yukie Akune4
, Kiyoko F. Aoki-Kinoshita4
, Frederique Lisacek2,5
and Nicolle H. Packer1,
*
1
Biomolecular Frontiers Research Centre, Macquarie University, North Ryde, NSW 2109, Australia, 2
Proteome
Informatics Group, Swiss Institute of Bioinformatics, Geneva, Switzerland, 3
Swiss-Prot Group, Swiss Institute of
Bioinformatics, Geneva, Switzerland, 4
Department of Bioinformatics, Faculty of Engineering, Soka University,
1-236 Tangi-machi, Hachioji, Tokyo, Japan and 5
Section of Biology, Faculty of Sciences, University of Geneva,
Switzerland
Received September 14, 2013; Revised October 18, 2013; Accepted October 24, 2013
ABSTRACT
The UniCarb KnowledgeBase (UniCarbKB; http://
unicarbkb.org) offers public access to a growing,
curated database of information on the glycan
structures of glycoproteins. UniCarbKB is an international
effort that aims to further our understanding
of structures, pathways and networks involved
in glycosylation and glyco-mediated processes by
integrating structural, experimental and functional
glycoscience information. This initiative builds
upon the success of the glycan structure database
GlycoSuiteDB, together with the informatic standards
introduced by EUROCarbDB, to provide
a high-quality and updated resource to support
glycomics and glycoproteomics research.
UniCarbKB provides comprehensive information
concerning glycan structures, and published glycoprotein
information including global and sitespecific
attachment information. For the first
release over 890 references, 3740 glycan structure
entries and 400 glycoproteins have been curated.
Further, 598 protein glycosylation sites have been
annotated with experimentally confirmed glycan
structures from the literature. Among these are 35
glycoproteins, 502 structures and 60 publications
previously not included in GlycoSuiteDB. This
article provides an update on the transformation of
GlycoSuiteDB (featured in previous NAR Database
issues and hosted by ExPASy since 2009) to
UniCarbKB and its integration with UniProtKB and
GlycoMod. Here, we introduce a refactored
database, supported by substantial new curated
data collections and intuitive user-interfaces that
improve database searching.
INTRODUCTION
Protein glycosylation is an important and universal posttranslational
modification that is estimated to occur on
between 20% and 50% (1,2) of all secreted and cellular
proteins. Glycoproteins are characterized by the presence
of oligosaccharides linked to the peptide backbone
through N- or O-glycosidic bonds at asparagine or
serine/threonine residues, respectively. For both N- and
O-glycosylation, there can be considerable diversity of
glycan structures associated with each glycosylation site.
Such micro-heterogeneity is governed by an elaborate
process carried out by numerous intricate and competitive
steps, which result in the generation of tissue and cell typespecific
glycan expression patterns.
Given that protein glycosylation is involved in
numerous cellular processes and is implicated in disease
progression (3–5), the ability to accurately characterize
glycan structures (at a global and site-specific manner)
and the identification of the modified proteins is increasingly
important in functional glycomics (6–8). The molecular
and functional complexity of glycoproteins is
challenging and requires sustainable bioinformatic resources
aimed at capturing, integrating and maintaining
the available knowledge. The more complete our understanding
of glycosylation is the better equipped we will be
to understand the functional and structural roles of both
glycoproteins and the attached glycans at the molecular
level. Unfortunately and despite the success of several
international initiatives the glycosciences still lack a
managed infrastructure that contributes to the advancement
of research through the provision of comprehensive
structural and experimental glycan data collections.
As described by the US National Academy of Sciences
report ‘Transforming Glycoscience: A Roadmap for the
Future’ (9) an important factor in broadening the appreciation
of glycomics is the necessity to develop robust,
scalable and standardized bioinformatic platforms to
*To whom correspondence should be addressed. Tel: +61 2 9850 8176; Fax: +61 2 9850 8313; Email: nicki.packer@mq.edu.au
Published online 13 November 2013 Nucleic Acids Research, 2014, Vol. 42, Database issue D215–D221
doi:10.1093/nar/gkt1128
ß The Author(s) 2013. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/
by-nc/3.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial
re-use, please contact journals.permissions@oup.com
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom
acquire and disseminate the information-rich data collections
that are becoming increasingly available.
OVERVIEW OF UniCarbKB
UniCarbKB is an initiative that aims to promote the
creation of a curated, glycan structure based, online information
storage and search platform for glycoscience
research (10). This initiative builds upon the previously
successful databases, the Australian developed
GlycoSuiteDB (11) and the EU-funded EUROCarbDB
(12), to offer a freely accessible updated platform built
with modern front and back-end technologies. The reengineered
framework offers an intuitive user-interface
with enhanced features and greater support for on-going
international efforts to establish common data standards
that will better integrate structural, experimental and
functional data collections.
GlycoSuiteDB
GlycoSuiteDB is acknowledged as the first effort to provide
detailed non-redundant, curated structural information
derived from the published literature on conjugated
glycans. The database connects glycan structure and biological
origin with protein specific information where
known. For each glycan structure (e.g. glycan type, mass
and composition), detailed information is provided on the
native and recombinant sources (i.e. tissue and/or cell
type, cell line, strain and disease state), with appropriate
links to Swiss-Prot/TrEMBL entries, a record of the
methods used to determine the structure, and the
PubMed ID of the cited publication. The design objectives
and functionality of GlycoSuiteDB has been published
in previous NAR database issues (11,13). Originally developed
commercially, it has since been made available
publicly through the ExPASy server (14). Access to
the content has not only preserved the efforts of the
curation team, but is now helping to seed the
UniCarbKB effort to build an up-to-date high-quality
resource for glycoscience.
EUROCarbDB
The EUROCarbDB project was a collaborative European
design study that focused on building the foundations of
a technical framework to support glycobioinformatic
activities. This resulted in the provision of sophisticated
open-source tools and structure encoding formats and
databases that, to date, continue to support several
facets of analytical glycomics. The architecture of the
EUROCarbDB database started to address stumbling
blocks impeding progress in glycomics by providing the
glycobiology community with (i) universal standards for
the representation of monosaccharides and complex
glycans, (ii) a freely accessible database of known glycan
structures and experimental evidence, (iii) freely accessible
analytical tools for researchers and (iv) a technical framework
of open-source code.
UniCarbKB: building upon the foundations laid by
GlycoSuiteDB and EUROCarbDB
UniCarbKB is focused on enhancing existing tools, standards
and applications to be more accessible and amenable
to modern research workflows. In particular we have
leveraged previous experiences to build a modern and
scalable framework, which uses technologies and web
frameworks that are more familiar to developers. As the
first step we have merged the glycan structural information
from the no longer supported GlycoSuiteDB and
EUROCarbDB initiatives into a high-quality updated
framework. Several libraries developed by the
EUROCarbDB initiative including GlycanBuilder (15),
MonosaccharideDB (http://www.monosaccharidedb.org)
and GlycoCT (16) have also been incorporated.
DESIGN AND IMPLEMENTATION
UniCarbKB is built with the open-source framework
Play (Release 2.1.3) written in Java and Scala, which
follows the model-view-controller architecture. The views
(user-interface) are predominantly written in Scala and
include JQuery and Bootstrap Javascript libraries. The
model and controller layers are written in Java and the
Ebean object-relational mapping (ORM) library is used to
query the underlying database model. UniCarbKB uses
PostgreSQL (Version 9.2) as the underlying database
system that consists of multiple schemas to ensure data
integrity by managing structural, literature and experimental
data collections.
We have updated the front-end of GlycoSuiteDB with a
refreshed interface that is easier to navigate and focuses on
displaying content the researcher wants to access. The new
update is more visual, includes new, simpler content
layout and improved accessibility options. All pages now
display a menu bar to make it easier to access features and
navigate around the website in a consistent way. The inclusion
of JavaScript libraries and Bootstrap has allowed
us to enhance the user experience. For example, we have
changed the search functionality by including an auto
completion feature in addition the use of pagination and
drop-down lists improve the handling and display of large
data collections. During the design process a series of
sketched user interface wireframes and mockups were
created, which allowed developers to consult with the
end-user to test and refine navigation, evaluate the effectiveness
of page layouts and determine web development/
programming requirements.
DATABASE CONTENT
Primarily, UniCarbKB is a eukaryotic glycoproteincentric
resource built on the corpus of curated information
originating from GlycoSuiteDB and a select few datasets
from EUROCarbDB. We have expanded the content by
manually curating over 60 more recent publications that
contain (partial or completely characterized) glycan structures
with supporting experimental data that substantially
extend the content coverage of GlycoSuiteDB. A majority
of the newly sourced data are derived from a literature
D216 Nucleic Acids Research, 2014, Vol. 42, Database issue
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom
study by Thaysen-Andersen and Packer, which sought to
correlate N-glycan structures characterized from purified
glycoproteins with protein structure (17). This comprehensive
dataset will contribute over 470 glycosylation sites
from over 160 mammalian glycoproteins, from different
tissues and body fluids to the over 3700 glycan structure
entries, 400 glycoproteins and 598 protein glycosylation
sites already curated by UniCarbKB. For each glycoprotein
record two levels of database annotations are
provided: (i) site-specific data for individual glycan structures
that are associated to an amino acid sequence position
and (ii) where a single purified glycoprotein has been
analysed, all characterized glycan structures are linked to
the glycoprotein accession number in UniProtKB (14).
Also, new structural and experimental glycan data have
been contributed from the integration of the final public
release of GlycoBase (18) developed in conjunction with
EUROCarbDB.
SEARCH FEATURES
As part of our effort to improve the overall user experience
a series of new interfaces have been implemented
(Figure 1). Many build upon and retain the features available
in GlycoSuiteDB but with improved functionality.
For example, we have (i) enhanced native selects by
including a multi-select interface (ii) made greater use of
Javascript to load items via Ajax supporting the ability to
partially load dataset and (iii) paginated for better support
of the presentation and navigation of large datasets.
Supported queries include (sub)structure, monosaccharide
composition, glycan mass, taxonomy, tissue, disease,
glycoprotein (accession number or Swiss-Prot name) and
literature publication.
Structure searching with GlycanBuilder
Previously, GlycoSuiteDB provided a structure interface
that consisted of textual and form based input, however,
many researchers prefer to graphically visualize glycan
structures due to their inherent complexity. We have
incorporated GlycanBuilder (Vaadin Release) (19) into
the search functionality of UniCarbKB that supports the
exact or partial matching of structures in the database.
The user may (i) build a new structure, (ii) extend a structure
from a predefined list or (iii) build a substructure/
epitope; in all instances the anomeric configuration of a
Figure 1. UniCarbKB offers a number of improved query interfaces. (A) Users can search the database content by monosaccharide composition,
attached protein, taxonomy or tissue by using an auto completion feature. (B) The integration of latest version of GlycanBuilder allows users to
query UniCarbKB by (sub)structure searching.
Nucleic Acids Research, 2014, Vol. 42, Database issue D217
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom
monosaccharide residue and linkage type can be defined.
By default an exact search will only retrieve those
database structures that perfectly match the topology,
linkage and anomeric configuration submitted. In the
case of partial searching, a level of fuzziness is introduced,
whereby unknown information is handled as wildcards by
the search algorithm. For substructure searching only
those structures that have the (extended) epitope or
motif built will be returned.
Glycan structure encoding
A plethora of graphical and textual formats are available
for the depiction of glycan structures including: the
Consortium for Functional Glycomics/Essentials, the
Oxford nomenclature and IUPAC formats. Historically,
GlycoSuiteDB encoded glycan structures in an IUPAC
style format, however, recent databases have adopted connection
table approaches exemplified by GlycoCT and
KCF (KEGG Chemical Function) (20) to describe oligosaccharide
sequences with a controlled vocabulary. By extension
of these efforts UniCarbKB supports the storage
of GlycoCT and IUPAC formats, and to further extend
database interoperability an IUPAC to KCF and a
modified IUPAC to GlycoCT translator have recently
been developed to complement existing translators.
Similar to GlycomeDB and EUROCarbDB we have implemented
a feature that enables users to switch between
supported graphical formats. This feature is made possible
by integrating the GlycanBuilder API, which produces
high-quality representations of glycan structures.
METADATA EXTENSIONS
To enable users of UniCarbKB to assess the reliability of
the contained information, provenance metadata must be
recorded. Provenance metadata relates to the origin of the
data and deals less with the finer details and more with the
process of how the data came to be.
Biological source
The biological context module, developed by
EUROCarbDB, handles the association of structure to
biological source that amalgamates taxonomy and tissue,
together with a varying number of disease and perturbation
associations (Figure 2). The library adopts the
controlled vocabularies derived from the NCBI
Taxonomy and the MeSH (Medical Subject Headings)
databases. Its inclusion reduces data redundancy by
providing a hierarchical controlled vocabulary that links
Figure 2. Screenshot for the Coagulation Factor IX entry in UniCarbKB. The database provides a description of the glycan structures characterized
for this glycoprotein and the number of structures associated with experimentally confirmed glycosylation sites. A general description of the
glycoprotein is provided that has been derived from the relevant UniProtKB entry in addition to the protein sequence. Users have the Structure
Format option to select a preferred graphical format to display the glycan structures that includes the three most commonly used notations.
Supporting biological metadata and publication information is also provided. The Biological Associations include details pertinent to the species,
the individual protein and tissue/secretory fluid source. Finally, those References that have been manually curated to obtain this information are
summarized with appropriate links to PubMed.
D218 Nucleic Acids Research, 2014, Vol. 42, Database issue
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom
specific taxonomic descriptions with more generalized
terms e.g. specific tumours or cancer of the lung are
grouped under the more general term ‘Lung Neoplasms’.
This approach improves upon the disconnected terms used
in GlycoSuiteDB, by proving a more robust interface to
searching and grouping together glycan structures based
on taxonomic or disease terms.
Identification of methods
The reporting of descriptive metadata that is representative
of the reported literature poses many challenges, but is
essential for the development of a well-documented glycan
and glycoprotein database. Efforts led by the Minimum
Information for A Glycomics Experiment (MIRAGE)
(21) project and the ontology work of GlycoRDF aim to
alleviate this situation by providing standardized data
entry terms, therefore fulfilling one of the recommendations
of the NAS Committee on Assessing the Importance
and Impact of Glycomics and Glycosciences. UniCarbKB
has started to address those standardization guidelines
proposed by MIRAGE, by establishing a high-level
vocabulary that captures (i) the sample preparation procedures;
encompassing glycan release techniques and/or
methods that alter glycan structure, including
exoglycosidase treatment and derivatization, (ii) the
general analytical approach and (iii) the use of complementary
validation methods such as lectin studies and
monosaccharide analysis. This information is provided
for all published references that have been curated and
the vocabulary is continually expanded to reflect
database content. By listing the methods used by the
authors of the publication to determine the structure,
users can determine their own level of confidence in the
reported structures; in particular, by assessing the suitability
of orthogonal methods such as array platforms, capillary
electrophoresis, gas chromatography, lectin-binding,
liquid chromatography, mass spectrometry and nuclear
magnetic resonance.
N-glycan pathways
GlycanSynth is a new feature in UniCarbKB that integrates
known genes and enzymes involved in the biosynthesis
of N-glycans. A list of enzymes was manually
curated from the Kyoto Encyclopedia of Genes and
Genomes (22) and GlycoGene (23) databases. Data
related to enzyme activity, including but not limited to
glycosylation-related processes were also catalogued
from the BRENDA (24) and UniProt databases. In
addition, the Consortium for Functional Glycomics (25)
and Carbohydrate-Active enzymes (26) were used as
valuable resources for extracting glycosyltransferase
genes and related downstream targets information.
Furthermore, we aggregated appropriate gene information
from the National Center for Biotechnology
Information (NBCI).
For each catalogued protein N-glycosylation-related
gene name we constructed a broad set of disaccharide reactions
that match gene against a particular donor and
acceptor substrate. In total, 37 glycosyltransferases have
been documented that are involved in the synthesis of
N-glycan structures in humans stemming from the Man5
structure. A list of these gene names, enzymes and reactions
is available at http://unicarbkb.org/enzymes. By
using these reaction rules it is possible to (i) connect
gene function with glycan structure and (ii) validate the
accuracy of structures in a database based on implicit
knowledge of the glycosylation machinery. This will be
achieved by encoding the disaccharide sequences in the
GlycoCT condensed format or IUPAC form, and using
a tree traversal technique to assign linkage information.
INTERFACING UNICARBKB WITH EXTERNAL
RESOURCES
Following the release of GlycoSuiteDB in 2002 several
international initiatives have developed structural and experimental
glycan databases notably the CFG,
EUROCarbDB, BCSDB (27), RINGS (28) and
JCGGDB. A key component of UniCarbKB is to forge
relationships with these valuable resources. In the first
instance we have worked with the glycan MS/MS data
repository, UniCarb-DB (29) and liquid chromatography
retention data collection, GlycoBase (18) (projects that
stemmed from EUROCarbDB) to cross-reference these
databases of experimental data together through structure-based
URL links in UniCarbKB. In partnership
with Australian National Data Service we have integrated
UniCarbKB curated data collections with Research Data
Australia—a discovery platform that enhances connections
between data projects, researchers and institutions
aimed at promoting the visibility of research. Also, the
GlycoMod tool (14) (hosted at ExPASy http://web.
expasy.org/glycomod) designed to predict oligosaccharides
structures from experimentally determined masses is
now directly linked to UniCarbKB; connecting theoretically
possible compositions with curated glycan structures.
Finally, we have also made use of the UniProtJAPI Java
web service (30), which facilitates the integration of
UniProtKB data into our web application. Here, we
extract the glycoprotein description from UniProtKB for
all glycan structure entries that have an assigned protein
accession number; such information is displayed to the
user in each protein summary page (Figure 3).
FUTURE DEVELOPMENTS
We envisage that this resource will be extended in the
future to encompass knowledge and information on all
glycoconjugates, however, due to limited resources the
emphasis initially will be placed on publications containing
well characterized N- and O-linked structures and the
associated experimental data on proteins derived from eukaryotic
organisms. UniCarbKB will be updated on a
regular basis with newly curated data collections. In the
short term, we will also enhance the functional information
of glycans by cross-linking the SugarBind database
(31) to UniCarbKB and target sub-structures recognized
by lectins.
We plan to make available a web service API this year to
support access to UniCarbKB data. By using the API
Nucleic Acids Research, 2014, Vol. 42, Database issue D219
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom
developers will be able to search against UniCarbKB and
its affiliated mass spectral-based project UniCarb-DB. In
conjunction with the GlycoRDF project we have started to
represent our data in a standardized Resource Description
Framework (RDF) format that will tackle the problems of
disparate and decentralized databases by using Semantic
Web technologies to unify content. We also plan to implement
support for new tools that utilize the growing information
stored in UniCarbKB e.g. ‘GlycoDigest’ (an
exoglycosidase digestion prediction tool in development at
SIB) and glycan translators that will support commonly
used encoding formats including WURCS (Web3.0
Unique Representation of Carbohydrate Structures). To
the best of our abilities, our development effort guarantees
data exchange and tool compatibility (32). In the longer
term we plan to establish UniCarbKB as a structurecentric,
high-quality glycan database from which all available
information on each glycan structure is easily
accessible.
ACKNOWLEDGEMENTS
The authors thank the support provided by many
developers and collaborators who have contributed
considerable effort to provide tools and resources for the
glycosciences. In particular we thank teams involved in
UniCarb-DB, GlycoBase, EUROCarbDB, GlycomeDB
and PubChem. Finally, the authors acknowledge the
efforts of MIRAGE and support from the Beilstein
Institut to develop guidelines and standards, and the
GlycoRDF project.
FUNDING
The Australian National eResearch Collaboration Tools
and Resources project [NeCTAR RT016 to M.P.C and
N.H.P]; Swiss National Science Foundation [SNSF
31003A_141215 J.M.]; Swiss Federal Government
through the State Secretariat for Education, Research
and Innovation SERI [F.L. and E.G.]; ExPASy is maintained
by the web team of the Swiss Institute of
Bioinformatics and hosted at the Vital-IT Competency
Center; UniCarbKB was also supported by Agilent’s
University Relations program to M.P.C and N.H.P;
GlycoSuiteDB was developed by Proteome Systems Ltd
[N.H.P] and transferred to SIB in 2009; EUROCarbDB
was originally funded by European Union as a Research
Infrastructure Design Study implemented as a Specific
Figure 3. Navigating from UniProtKB to UniCarbKB. An example is shown for the (A) UniProtKB alpha-2-HS-glycoprotein entry that is linked to
(B) the glycan structures on the individual amino acid sites as curated in UniCarbKB, by CAR identifiers. The curated records in the first release of
UniCarbKB are being updated and included in the sequence annotation feature records of UniProtKB.
D220 Nucleic Acids Research, 2014, Vol. 42, Database issue
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom
Support Action under the FP6 Research Framework
Program (RIDS Contract number 011952). Funding
for open access charge: Australian National
eResearch Collaboration Tools and Resources
[NeCTAR RT016].
Conflict of interest statement. None declared.
REFERENCES
1. Khoury,G.A., Baliban,R.C. and Floudas,C.A. (2011) Proteomewide
post-translational modification statistics: frequency analysis
and curation of the swiss-prot database. Sci. Rep., 1, 90.
2. Apweiler,R., Hermjakob,H. and Sharon,N. (1999) On the
frequency of protein glycosylation, as deduced from analysis of
the SWISS-PROT database. Biochim. Biophys. Acta., 1473, 4–8.
3. Fuster,M.M. and Esko,J.D. (2005) The sweet and sour of cancer:
glycans as novel therapeutic targets. Nat. Rev. Cancer, 5,
526–542.
4. Dube,D.H. and Bertozzi,C.R. (2005) Glycans in cancer and
inflammation–potential for therapeutics and diagnostics. Nat. Rev.
Drug Discov., 4, 477–488.
5. Raman,R., Raguram,S., Venkataraman,G., Paulson,J.C. and
Sasisekharan,R. (2005) Glycomics: an integrated systems approach
to structure-function relationships of glycans. Nat. Mehods, 2,
817–824.
6. Kolarich,D., Jensen,P.H., Altmann,F. and Packer,N.H. (2012)
Determination of site-specific glycan heterogeneity on
glycoproteins. Nat. Protoc., 7, 1285–1298.
7. An,H.J., Froehlich,J.W. and Lebrilla,C.B. (2009) Determination
of glycosylation sites and site-specific heterogeneity in
glycoproteins. Curr. Opin. Chem. Biol., 13, 421–426.
8. Dwek,R.A. (1996) Glycobiology: toward understanding the
function of sugars. Chem. Rev., 96, 683–720.
9. Transforming Glycoscience: A Roadmap for the Future (2012),
Washington (DC).
10. Campbell,M.P., Hayes,C.A., Struwe,W.B., Wilkins,M.R., AokiKinoshita,K.F.,
Harvey,D.J., Rudd,P.M., Kolarich,D., Lisacek,F.,
Karlsson,N.G. et al. (2011) UniCarbKB: putting the pieces
together for glycomics research. Proteomics, 11, 4117–4121.
11. Cooper,C.A., Harrison,M.J., Wilkins,M.R. and Packer,N.H.
(2001) GlycoSuiteDB: a new curated relational database of
glycoprotein glycan structures and their biological sources.
Nucleic Acids Res., 29, 332–335.
12. von der Lieth,C.W., Freire,A.A., Blank,D., Campbell,M.P.,
Ceroni,A., Damerell,D.R., Dell,A., Dwek,R.A., Ernst,B., Fogh,R.
et al. (2011) EUROCarbDB: an open-access platform for
glycoinformatics. Glycobiology, 21, 493–502.
13. Cooper,C.A., Joshi,H.J., Harrison,M.J., Wilkins,M.R. and
Packer,N.H. (2003) GlycoSuiteDB: a curated relational database
of glycoprotein glycan structures and their biological sources.
2003 update. Nucleic Acids Res., 31, 511–513.
14. Artimo,P., Jonnalagedda,M., Arnold,K., Baratin,D., Csardi,G., de
Castro,E., Duvaud,S., Flegel,V., Fortier,A., Gasteiger,E. et al.
(2012) ExPASy: SIB bioinformatics resource portal. Nucleic Acids
Res., 40, W597–W603.
15. Ceroni,A., Dell,A. and Haslam,S.M. (2007) The GlycanBuilder: a
fast, intuitive and flexible software tool for building and
displaying glycan structures. Source Code Biol. Med., 2, 3.
16. Herget,S., Ranzinger,R., Maass,K. and von der Lieth,C.-W.
(2008) GlycoCT-a unifying sequence format for carbohydrates.
Carbohydr. Res., 343, 2162–2171.
17. Thaysen-Andersen,M. and Packer,N.H. (2012) Site-specific
glycoproteomics confirms that protein structure dictates formation
of N-glycan type, core fucosylation and branching. Glycobiology,
22, 1440–1452.
18. Campbell,M.P., Royle,L., Radcliffe,C.M., Dwek,R.A. and
Rudd,P.M. (2008) GlycoBase and autoGU: tools for HPLC-based
glycan analysis. Bioinformatics, 24, 1214–1216.
19. Damerell,D., Ceroni,A., Maass,K., Ranzinger,R., Dell,A. and
Haslam,S.M. (2012) The GlycanBuilder and GlycoWorkbench
glycoinformatics tools: updates and new developments. Biol
Chem, 393, 1357–1362.
20. Aoki-Kinoshita,K.F. (2010) Glycome Informatics: Methods and
Applications. Chapman & Hall, London.
21. Kolarich,D., Rapp,E., Struwe,W.B., Haslam,S.M., Zaia,J.,
McBride,R., Agravat,S., Campbell,M.P., Kato,M., Ranzinger,R.
et al. (2013) The minimum information required for a glycomics
experiment (MIRAGE) project: improving the standards for
reporting mass-spectrometry-based glycoanalytic data. Mol. Cell.
Proteomics, 12, 991–995.
22. Kanehisa,M. and Goto,S. (2000) KEGG: kyoto encyclopedia of
genes and genomes. Nucleic Acids Res., 28, 27–30.
23. Narimatsu,H. (2004) Construction of a human glycogene library
and comprehensive functional analysis. Glycoconj. J., 21, 17–24.
24. Schomburg,I., Chang,A., Placzek,S., Sohngen,C., Rother,M.,
Lang,M., Munaretto,C., Ulas,S., Stelzer,M., Grote,A. et al. (2013)
BRENDA in 2013: integrated reactions, kinetic data, enzyme
function data, improved disease classification: new options and
contents in BRENDA. Nucleic Acids Res., 41, D764–D772.
25. Raman,R., Venkataraman,M., Ramakrishnan,S., Lang,W.,
Raguram,S. and Sasisekharan,R. (2006) Advancing glycomics:
implementation strategies at the consortium for functional
glycomics. Glycobiology, 16, 82R–90R.
26. Cantarel,B.L., Coutinho,P.M., Rancurel,C., Bernard,T.,
Lombard,V. and Henrissat,B. (2009) The Carbohydrate-Active
EnZymes database (CAZy): an expert resource for
Glycogenomics. Nucleic Acids Res., 37, D233–D238.
27. Toukach,F.V. and Knirel,Y.A. (2005) New database of bacterial
carbohydrate structures. Glycoconj. J., 22, 216–217.
28. Akune,Y., Hosoda,M., Kaiya,S., Shinmachi,D. and AokiKinoshita,K.F.
(2010) The RINGS resource for glycome
informatics analysis and data mining on the Web. Omics, 14,
475–486.
29. Hayes,C.A., Karlsson,N.G., Struwe,W.B., Lisacek,F., Rudd,P.M.,
Packer,N.H. and Campbell,M.P. (2011) UniCarb-DB: a database
resource for glycomic discovery. Bioinformatics, 27, 1343–1344.
30. Patient,S., Wieser,D., Kleen,M., Kretschmann,E., Jesus Martin,M.
and Apweiler,R. (2008) UniProtJAPI: a remote API for accessing
UniProt data. Bioinformatics, 24, 1321–1322.
31. Shakhsheer,B., Anderson,M., Khatib,K., Tadoori,L., Joshi,L.,
Lisacek,F., Hirschman,L. and Mullen,E. (2013) SugarBind
database (SugarBindDB): a resource of pathogen lectins and
corresponding glycan targets. J. Mol. Recognit., 26, 426–431.
32. Campbell,M.P., Ranzinger,R., Lutteke,T., Mariethoz,J.,
Hayes,C.A., Zhang,J., Akune,Y., Aoki-Kinoshita,K.F.,
Damerell,D., Carta,G. et al. Toolboxes for a standardised and
systematic study of glycans. BMC Bioinformatics.
Nucleic Acids Research, 2014, Vol. 42, Database issue D221
atMasarykUniversityonMay6,2014http://nar.oxfordjournals.org/Downloadedfrom