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https://github.com/bojarlab/scglycomics_b16_branching

Predicting single-cell glycosylation features from scRNA-seq

https://github.com/bojarlab/scglycomics_b16_branching

Science Score: 13.0%

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deep-learning glycans glycobiology machine-learning
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Predicting single-cell glycosylation features from scRNA-seq

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  • Host: GitHub
  • Owner: BojarLab
  • License: mit
  • Language: Jupyter Notebook
  • Default Branch: main
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  • Size: 2.35 MB
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deep-learning glycans glycobiology machine-learning
Created about 4 years ago · Last pushed about 4 years ago

https://github.com/BojarLab/scGlycomics_b16_branching/blob/main/ 

# Deep Learning Explains the Biology of Branched Glycans from Single-Cell Sequencing Data

This repository contains the code and the trained model from our recent preprint "Deep Learning Explains the Biology of Branched Glycans from Single-Cell Sequencing Data" (Qin et al., 2022), made by https://github.com/rruiqin. In this work, we demonstrate a method to gain insight into the multimodal role of glycans by analyzing paired single-cell transcriptomics data and lectin-sequencing via a dedicated deep learning model.

The processed RNA and PHA-L reads can be found [here](https://doi.org/10.7303/syn32244556.1).

Owner

  • Name: BojarLab
  • Login: BojarLab
  • Kind: organization
  • Email: daniel.bojar@gu.se
  • Location: Gothenburg, Sweden

Machine Learning in Glycobiology and Systems Biology

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