🦠 Model Request: Pre-trained knowledge-guided graph transformer for molecular representation

[miquelduranfrigola]

Model Name

Knowledge-guided pre-trained graph transformer

Model Description

Neural fingerprints (embeddings) based on a knowledge-guided graph transformer. This model reprsents a novel self-supervised learning framework for the representation learning of molecular graphs, consisting of a novel graph transformer architecture, LiGhT, and a knowledge-guided pre-training strategy.

Slug

kgpgt-embedding

Tag

Descriptor

Publication

https://www.nature.com/articles/s41467-023-43214-1

Source Code

https://github.com/lihan97/KPGT

License

Apache-2.0

[miquelduranfrigola]

/approve

[github-actions]

New Model Repository Created! 🎉

@miquelduranfrigola ersilia model respository has been successfully created and is available at:

🔗 ersilia-os/eos8aa5

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[miquelduranfrigola]

I am working on this model. Encountering issues with DGL library on a Mac, so probably will have to develop this model on Linux.

[miquelduranfrigola]

Update: I have successfully run the model on the raluy computer (Ubuntu, GPU). The goal is to finalize the packaging by 18/12/2024.

[miquelduranfrigola]

I have done most of the necessary work, including the install.yml file and the relatively complex run.sh: https://github.com/ersilia-os/eos8aa5

Now I have realized that Ersilia Pack requires a Python version greater than 3.7: https://github.com/ersilia-os/eos8aa5/actions/runs/12391375778/job/34588326502

We need to figure this out.