2018
DOI: 10.1021/acs.jproteome.8b00766
|View full text |Cite
|
Sign up to set email alerts
|

GlyConnect: Glycoproteomics Goes Visual, Interactive, and Analytical

Abstract: Knowledge of glycoproteins, their site-specific glycosylation patterns and the glycan structures that they present to their recognition partners in health and disease are gradually being built on using a range of experimental approaches. The data from these analyses are increasingly being standardised and presented in various sources, from supplemental tables in publications to localised servers in investigator laboratories. Bioinformatics tools are now needed to collect this data and enable the user to search… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
3
1

Citation Types

2
98
0

Year Published

2019
2019
2024
2024

Publication Types

Select...
6
3

Relationship

1
8

Authors

Journals

citations
Cited by 114 publications
(100 citation statements)
references
References 47 publications
2
98
0
Order By: Relevance
“…These complexities are very difficult to resolve, requiring high levels of expertise and multi-layered orthogonal approaches [8][9][10]7]. Within this framework, the contribution of glycoinformatics tools and databases represents an essential resource to advance glycomics [11][12][13][14][15], while molecular simulations fit in very well as complementary and orthogonal techniques to support and advance structural glycobiology research. Indeed, current high performance computing (HPC) technology allows us to study realistic model systems [16,17] and to reach experimental timescales [18], so that computing can now contribute as one of the leading research methods in structural glycobiology.…”
Section: Introductionmentioning
confidence: 99%
“…These complexities are very difficult to resolve, requiring high levels of expertise and multi-layered orthogonal approaches [8][9][10]7]. Within this framework, the contribution of glycoinformatics tools and databases represents an essential resource to advance glycomics [11][12][13][14][15], while molecular simulations fit in very well as complementary and orthogonal techniques to support and advance structural glycobiology research. Indeed, current high performance computing (HPC) technology allows us to study realistic model systems [16,17] and to reach experimental timescales [18], so that computing can now contribute as one of the leading research methods in structural glycobiology.…”
Section: Introductionmentioning
confidence: 99%
“…GlyConnect (https://glyconnect .expasy.org/) is the central platform for glycoinformatics. It has been developed to gather, monitor, integrate, and visualize glycomics data and to integrate multiple data types (Alocci et al, 2019). Major web-based glycan resources are reviewed in Bennun et al (2016) and include the following: GlycomeDB, GlycoSuiteDB, Japan Consortium for Glycobiology and Glycotechnology Database ( JCGGDB), and Complex Carbohydrate Structure Database (CCSD; CarbBank).…”
Section: Bioinformatics Tools and Databasesmentioning
confidence: 99%
“…We describe here a web-based tool destined to assist glycoproteomics software users in selecting appropriate N-or O-linked glycan compositions with respect to sample specifications encompassing species, tissue or cell line type and disease. This tool named Compozitor, relies on the data collected in the GlyConnect resource (10), which includes glycomics and glycoproteomics data. In fact, Compozitor reveals global glycomic information associated with a species, a glycoprotein, a cell or a tissue that cannot be captured when reading through the corresponding GlyConnect entries.…”
Section: Introductionmentioning
confidence: 99%
“…In particular, a glycome is often provided as a list of glycan structures or a list of compositions or a mix thereof, as if the items were independent when they obviously are not. The interface of GlyConnect described in (10) was a first attempt to link and visualise glycomic and proteomic data, e.g., addressing the question of which glycan(s) is/are attached to which protein(s). Navigation in the database did not support the comparative investigation of structural data dependencies, e.g., addressing the question of detecting glycan compositional trends within and similarities across protein(s) or tissues.…”
Section: Introductionmentioning
confidence: 99%