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Scientific article
English

This is GlycoQL

Published inBioinformatics, vol. 38, no. Supplement_2, no. Proceedings of ECCB2022, p. ii162-ii167
Publication date2022-09-01
First online date2022-09-18
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/.

eng
Citation (ISO format)
HAYES, Catherine et al. This is GlycoQL. In: Bioinformatics, 2022, vol. 38, n° Supplement_2, p. ii162–ii167. doi: 10.1093/bioinformatics/btac500
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ISSN of the journal1367-4803
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