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06.01.2026: Equivariant Models, Protein and RNA Structure Prediction, and Large Language Models for Molecular Applications
This podcast is brought to you by the Oliver Laboratory at Vanderbilt University.
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0:00 Deep Learning Framework for RNA Inverse Folding with Geometric Structure Potentials (https://arxiv.org/pdf/2601.00895.pdf)
4:56 MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics (https://arxiv.org/pdf/2601.02075.pdf)
10:05 Edge-aware GAT-based protein binding site prediction (https://arxiv.org/pdf/2601.02138.pdf)
14:23 Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction (https://arxiv.org/pdf/2601.02213.pdf)
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Source code: https://github.com/OliverLaboratory/arxivreader
Contact: oliverlaboratory.com
Source code: https://github.com/OliverLaboratory/arxivreader
View all episodes
By This podcast is brought to you by the Oliver Laboratory at Vanderbilt University.
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0:00 Deep Learning Framework for RNA Inverse Folding with Geometric Structure Potentials (https://arxiv.org/pdf/2601.00895.pdf)
4:56 MDAgent2: Large Language Model for Code Generation and Knowledge Q&A in Molecular Dynamics (https://arxiv.org/pdf/2601.02075.pdf)
10:05 Edge-aware GAT-based protein binding site prediction (https://arxiv.org/pdf/2601.02138.pdf)
14:23 Quantized SO(3)-Equivariant Graph Neural Networks for Efficient Molecular Property Prediction (https://arxiv.org/pdf/2601.02213.pdf)
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Source code: https://github.com/OliverLaboratory/arxivreader
Contact: oliverlaboratory.com
Source code: https://github.com/OliverLaboratory/arxivreader