Hayes C, Daponte V, Mariethoz J, Lisacek F. This is GlycoQL.
Bioinformatics 2022;
38:ii162-ii167. [PMID:
36124803 DOI:
10.1093/bioinformatics/btac500]
[Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022] Open
Abstract
MOTIVATION
We have previously designed and implemented a tree-based ontology to represent glycan structures with the aim of searching these structures with a glyco-driven syntax. This resulted in creating the GlySTreeM knowledge-base as a linchpin of the structural matching procedure and we now introduce a query language, called GlycoQL, for the actual implementation of a glycan structure search.
RESULTS
The methodology is described and illustrated with a use-case focused on Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) spike protein glycosylation. We show how to enhance site annotation with federated queries involving UniProt and GlyConnect, our glycoprotein database.
AVAILABILITY AND IMPLEMENTATION
https://glyconnect.expasy.org/glycoql/.
Collapse