Discover a curated collection of pre-built queries designed to streamline your graph database searches using our advanced mode. As you type in the search bar, relevant query names will be suggested to assist you in selecting the most suitable operation. For those seeking more tailored results, you can also create and save your own custom queries.
Turn off this feature in the preferences if you don’t want to have these queries suggested.
Note that anonymity is limited to the current machine and browser; your data will be deleted after 1 week without an account.
GlyConnect is a curated database, collecting information in publications, from which pieces of evidence that describe specific aspects of glycosylation are extracted. Here's how we build it:
The list of nodes connected to Evidence nodes are listed below with their colour codes:
This structure allows us to organize complex scientific information into clear, searchable relationships, helping you find precise answers to your queries.
GlyConnect is developed using the Memgraph graph database management system, taking advantage of its capabilities for efficient storage and querying of graph-structured data. The Database Schema is visible upon clicking on the upper right of the search homepage.
The graph database search system is built on Cypher®, the graph query language developed for Neo4j. The engine may run in three modes:
Enter terms to enable the search engine to conduct a full-text search across one or more node types.
Please refer to the Pattern Matching System section below for more details.
One or more data types must be selected for searching a term. The invert button can be used to quickly select multiple types at once.
Only the graph nodes matching the search can be presented in the results.
For example:
antigen
.antigen
.membrane
.
The graph query language includes an intuitive builder that streamlines the query creation process. In guided search mode, both graph nodes and edges are searchable. As keywords are typed, the system offers suggestions for relevant node types, field names, accessible nodes, and even stored Cypher queries. At each step, the selected term must be validated to progressively build the query.
Please refer to the Pattern Matching System section below for more details.
For example:
Taxon
.Taxon
that contain the term 'human'Taxon
where the field name
contains the term 'human'Taxon
nodes to any CellComponent
nodes
Cypher® is Neo4j’s declarative query language, allowing users to unlock the full potential of property graph databases. We have chosen Memgraph as our graph database solution which allows for optimized performance and faster query execution, especially for real-time data handling. Memgraph uses openCypher an open source implementation of Cypher® but we will refer to it as Cypher for simplicity.
The advanced search mode relies on graph query methods for optimal searching. The documentation on Cypher syntax can be found here.
A selection of stored queries can be accessed by clicking from the sidebar area.
The search query system allows for flexible searches using special symbols to define term relationships.
A space between terms indicates a disjunctive search, where at least one term must appear in the document.
For example:
immunoglobulin
, gamma
, or both.The +
symbol defines a conjunctive search, requiring all terms to be present.
For example:
immunoglobulin
and gamma
.Anchors refine searches by specifying term positions:
>
anchor ensures the term appears at the beginning of the document.<
anchor forces the term to appear at the end of the document.For example:
immunoglobulin
.immunoglobulin
.immunoglobulin
.immunoglobulin
appears anywhere in the text.We currently support three navigation modes: paginated view, infinite scrolling, and graph view.
For a more immersive experience, we offer several guided tours, three of which explain the three search modes. These tours are accessible by clicking the directions icon at the top left. If any tours are incomplete, the icon will blink and indicate how many tours are still available.
Discover a curated collection of pre-built queries designed to streamline your graph database searches using our advanced mode. As you type in the search bar, relevant query names will be suggested to assist you in selecting the most suitable operation. For those seeking more tailored results, you can also create and save your own custom queries.
Turn off this feature in the preferences if you don’t want to have these queries suggested.
Note that anonymity is limited to the current machine and browser; your data will be deleted after 1 week without an account.
GlyConnect is a curated database, collecting information in publications, from which pieces of evidence that describe specific aspects of glycosylation are extracted. Here's how we build it:
The list of nodes connected to Evidence nodes are listed below with their colour codes:
This structure allows us to organize complex scientific information into clear, searchable relationships, helping you find precise answers to your queries.
GlyConnect is developed using the Memgraph graph database management system, taking advantage of its capabilities for efficient storage and querying of graph-structured data. The Database Schema is visible upon clicking on the upper right of the search homepage.
The graph database search system is built on Cypher®, the graph query language developed for Neo4j. The engine may run in three modes:
Enter terms to enable the search engine to conduct a full-text search across one or more node types.
Please refer to the Pattern Matching System section below for more details.
One or more data types must be selected for searching a term. The invert button can be used to quickly select multiple types at once.
Only the graph nodes matching the search can be presented in the results.
For example:
antigen
.antigen
.membrane
.
The graph query language includes an intuitive builder that streamlines the query creation process. In guided search mode, both graph nodes and edges are searchable. As keywords are typed, the system offers suggestions for relevant node types, field names, accessible nodes, and even stored Cypher queries. At each step, the selected term must be validated to progressively build the query.
Please refer to the Pattern Matching System section below for more details.
For example:
Taxon
.Taxon
that contain the term 'human'Taxon
where the field name
contains the term 'human'Taxon
nodes to any CellComponent
nodes
Cypher® is Neo4j’s declarative query language, allowing users to unlock the full potential of property graph databases. We have chosen Memgraph as our graph database solution which allows for optimized performance and faster query execution, especially for real-time data handling. Memgraph uses openCypher an open source implementation of Cypher® but we will refer to it as Cypher for simplicity.
The advanced search mode relies on graph query methods for optimal searching. The documentation on Cypher syntax can be found here.
A selection of stored queries can be accessed by clicking from the sidebar area.
The search query system allows for flexible searches using special symbols to define term relationships.
A space between terms indicates a disjunctive search, where at least one term must appear in the document.
For example:
immunoglobulin
, gamma
, or both.The +
symbol defines a conjunctive search, requiring all terms to be present.
For example:
immunoglobulin
and gamma
.Anchors refine searches by specifying term positions:
>
anchor ensures the term appears at the beginning of the document.<
anchor forces the term to appear at the end of the document.For example:
immunoglobulin
.immunoglobulin
.immunoglobulin
.immunoglobulin
appears anywhere in the text.We currently support three navigation modes: paginated view, infinite scrolling, and graph view.
For a more immersive experience, we offer several guided tours, three of which explain the three search modes. These tours are accessible by clicking the directions icon at the top left. If any tours are incomplete, the icon will blink and indicate how many tours are still available.