Sign in
BioinformaticsGlycobiology
Peer-reviewed journal article

GlycoDraw: A Python Implementation for Generating High-Quality Glycan Figures

Jon LundstrømiD, James UrbaniD, Luc ThomèsiD, Daniel BojariD

Abstract

Glycans are essential to all scales of biology, with their intricate structures being crucial for their biological functions. The structural complexity of glycans is communicated through simplified and unified visual representations according to the Symbol Nomenclature for Glycans (SNFG) guidelines adopted by the community. Here, we introduce GlycoDraw, a Python-native implementation for high-throughput generation of high-quality, SNFG-compliant glycan figures with flexible display options. GlycoDraw is released as part of our glycan analysis ecosystem, glycowork, facilitating integration into existing workflows by enabling fully automated annotation of glycan-related figures and thus assisting the analysis of e.g., differential abundance data or glycomics mass spectra.

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers
Citations
24
FWCI
2.13
Field percentile
top 11%

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISThomès '21Bennett '24Loponte '25Bonner '24Joeres '22Ashwood '26
67% semantic matchBioinformatics
Luc Thomès, Rebekka Burkholz, Daniel Bojar·Glycobiology·Jun 25, 2021· 60 citations