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

Montreal
Joined February 2023
RT @carlosgoliver: @rnaglib is at #ISMBECCB2025! Head over to Luis Wyss' poster tomorrow to learn how we opening RNA structures to deep lea…
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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.
🚨 New paper 🚨 RNA modeling just got its own Gym! 🏋️ Introducing RNAGym, large-scale benchmarks for RNA fitness and structure prediction. 🧵 1/9
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RNA Geometric Library retweeted
.@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: arxiv.org/pdf/2503.21681
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RT @carlosgoliver: Big new upgrade for @rnaglib. Our new 'Task' module supports benchmarking deep learning models of RNA 3D structures ef…
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Congrats, RNAmigos team! Glad I could be of help!
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: nature.com/articles/s41467-0… GitHub: github.com/cgoliver/rnamigos… 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.
There's a new version of this post
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Many new features for AI model training and benchmarking coming soon. Stay tuned.
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RNA Geometric Library retweeted
Agreed. For rna-centric graph benchmarks (preprint soon): rnaglib.org for protein-centric graph benchmarks: proteinshake.ai
* Graph Learning Will Lose Relevance Due To Poor Benchmarks * Maya Bechler-Speicher, @benfinkelshtein, @ffabffrasca, Luis Muller, et al. Inc. @mmbronstein @phanein @michael_galkin @chrsmrrs Wow we should be discussing / acting on this!
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RNA Geometric Library retweeted
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!
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