期刊
BIOINFORMATICS
卷 38, 期 -, 页码 ii162-ii167出版社
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btac500
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资金
- ECCB2022
- Swiss National Science Foundation (SNSF) [443 #31003A/179249]
- Swiss Federal Government through the State Secretariat for Education, Research and Innovation (SERI)
This article introduces a query language called GlycoQL for glycan structure search and describes the methodology with a focus on SARS-CoV-2 spike protein glycosylation.
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.
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