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This is GlycoQL.
Hayes, Catherine; Daponte, Vincenzo; Mariethoz, Julien; Lisacek, Frederique.
  • Hayes C; Department of Computer Science, University of Geneva, Geneva 1227, Switzerland.
  • Daponte V; Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland.
  • Mariethoz J; Department of Computer Science, University of Geneva, Geneva 1227, Switzerland.
  • Lisacek F; Proteome Informatics Group, SIB Swiss Institute of Bioinformatics, Geneva 1211, Switzerland.
Bioinformatics ; 38(Supplement_2): ii162-ii167, 2022 Sep 16.
Article in English | MEDLINE | ID: covidwho-20236649
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/.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Limits: Humans Language: English Journal: Bioinformatics Journal subject: Medical Informatics Year: 2022 Document Type: Article Affiliation country: Bioinformatics

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Full text: Available Collection: International databases Database: MEDLINE Main subject: SARS-CoV-2 / COVID-19 Limits: Humans Language: English Journal: Bioinformatics Journal subject: Medical Informatics Year: 2022 Document Type: Article Affiliation country: Bioinformatics