https://github.com/bojarlab/sweetnet
Graph convolutional neural networks for analyzing glycans [LEGACY; use glycowork implementation]
Science Score: 23.0%
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✓DOI references
Found 1 DOI reference(s) in README -
✓Academic publication links
Links to: biorxiv.org -
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○Scientific vocabulary similarity
Low similarity (3.7%) to scientific vocabulary
Keywords
bioinformatics
glycans
glycobiology
machine-learning
Last synced: 10 months ago
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Repository
Graph convolutional neural networks for analyzing glycans [LEGACY; use glycowork implementation]
Basic Info
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- Stars: 17
- Watchers: 2
- Forks: 6
- Open Issues: 1
- Releases: 0
Archived
Topics
bioinformatics
glycans
glycobiology
machine-learning
Created over 5 years ago
· Last pushed over 5 years ago
Metadata Files
Readme
License
README.md
SweetNet - A Graph Convolutional Neural Network for Analyzing Glycan Sequences
Contains code, data, and trained models to apply graph convolutional neural networks to glycan classification / regression tasks. Further information can be found in Burkholz et al., 2021. Helper functions stem from glycowork.
Owner
- Name: BojarLab
- Login: BojarLab
- Kind: organization
- Email: daniel.bojar@gu.se
- Location: Gothenburg, Sweden
- Website: https://dbojar.com/bojar-lab/
- Twitter: daniel_bojar
- Repositories: 4
- Profile: https://github.com/BojarLab
Machine Learning in Glycobiology and Systems Biology