Protocol for constructing glycan biosynthetic networks using glycowork.

Bioinformatics Evolutionary biology Sequence analysis

Journal

STAR protocols
ISSN: 2666-1667
Titre abrégé: STAR Protoc
Pays: United States
ID NLM: 101769501

Informations de publication

Date de publication:
15 Apr 2024
Historique:
received: 10 12 2023
revised: 09 01 2024
accepted: 19 02 2024
medline: 17 4 2024
pubmed: 17 4 2024
entrez: 17 4 2024
Statut: aheadofprint

Résumé

Glycans, present across all domains of life, comprise a wide range of monosaccharides assembled into complex, branching structures. Here, we present an in silico protocol to construct biosynthetic networks from a list of observed glycans using the Python package glycowork. We describe steps for data preparation, network construction, feature analysis, and data export. This protocol is implemented in Python using example data and can be adapted for use with customized datasets. For complete details on the use and execution of this protocol, please refer to Thomès et al.

Identifiants

pubmed: 38630592
pii: S2666-1667(24)00102-3
doi: 10.1016/j.xpro.2024.102937
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

102937

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests The authors declare no competing interests.

Auteurs

Jon Lundstrøm (J)

Department of Chemistry and Molecular Biology, University of Gothenburg, 41390 Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 41390 Gothenburg, Sweden. Electronic address: jon.lundstrom@gu.se.

Luc Thomès (L)

University Lille, CHU Lille, ULR 7364 - RADEME - Maladies RAres du DÉveloppement embryonnaire et du Métabolisme, 59000 Lille, France.

Daniel Bojar (D)

Department of Chemistry and Molecular Biology, University of Gothenburg, 41390 Gothenburg, Sweden; Wallenberg Centre for Molecular and Translational Medicine, University of Gothenburg, 41390 Gothenburg, Sweden. Electronic address: daniel.bojar@gu.se.

Classifications MeSH