RNA Geometric Library

Toolkit for geometric deep learning on RNA 3D structures. Follow for support and updates.

[RNA Geometric Library @rnaglib]

RT @carlosgoliver: @rnaglib is at #ISMBECCB2025! Head over to Luis Wyss' poster tomorrow to learn how we opening RNA structures to deep lea…

[RNA Geometric Library @rnaglib]

Happy to see more ML benchmarking methods for RNA from @NotinPascal !

While @rnaglib focuses on structure -> function;

RNAgym will be a great resource for sequence -> structure/fitness.

[Pascal Notin @NotinPascal]

🚨 New paper 🚨 RNA modeling just got its own Gym! 🏋️ Introducing RNAGym, large-scale benchmarks for RNA fitness and structure prediction.
🧵 1/9

[RNA Geometric Library @rnaglib]

Very impressed by the automatic wiki for rnaglib from @cognition_labs !

https://t.co/g77QKJfDb1

[Carlos Oliver @carlosgoliver]

.@RNAglib is now your best friend for building AI models of RNA structure-function.

To learn more, check out Luis Wyss' poster at @ai4na_workshop #ICLR25, "A Comprehensive Library for RNA Structure-Function Modeling":

When/where: morning poster session Monday, Apr 28th
Paper: https://t.co/7qmayQSSse

[RNA Geometric Library @rnaglib]

https://t.co/2LYxfGdiqU has hit 30 stars!

[RNA Geometric Library @rnaglib]

RT @carlosgoliver: Big new upgrade for @rnaglib.

Our new 'Task' module supports benchmarking deep learning models of RNA 3D structures ef…

[RNA Geometric Library @rnaglib]

Congrats, RNAmigos team! Glad I could be of help!

[Carlos Oliver @carlosgoliver]

Our latest efforts in AI-driven RNA drug discovery (RNAmigos2) have been published in Nature Communications.

Blessed to have worked with such a talented team: @MalletVincent, J. Waldispühl, JG Patiño, et al.

Paper: https://t.co/kv5Gqltqtj
GitHub: https://t.co/Yl5INi3bAf
Powered by: @rnaglib

Takeaways:

1. We achieve 10,000x speedup over docking at similar accuracies + boost ligand diversity over docking alone.
2. New benchmark test generalization to new structures.
3. Successful zero-shot active enrichment on in-vitro assay.
4. Multi-modal data, self-supervision, and synthetic data are key.
5. Docking and AI models work well side-by-side if you have the budget.

[RNA Geometric Library @rnaglib]

Many new features for AI model training and benchmarking coming soon. Stay tuned.

[Carlos Oliver @carlosgoliver]

Agreed.

For rna-centric graph benchmarks (preprint soon): https://t.co/17SQhjz6EO
for protein-centric graph benchmarks: https://t.co/giPJgfnhDe

[RNA Geometric Library @rnaglib]

rnaglib now lives at https://t.co/sIAjNAohB1!

[Munich RNA Club @MunichRNA]

Take out your agendas for the next #MunichRNA18S!
📍@HelmholtzMunich
📅18/09 15h

Come hear the amazing science from Gheo (Engelhardt's group @TU_Muenchen), David (@theNiessingLabs), Imesha (Lamb's group @LMU_Muenchen), Marc Schmidt-Supprian (TUM), and @carlosgoliver!

[RNA Geometric Library @rnaglib]

pip install rnaglib