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Workshop
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ContactNet: Geometric-Based Deep Learning Model for Predicting Protein-Protein Interactions
Matan Halfon · Dina Schneidman · Tomer Cohen · raanan fattal
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Affinity Workshop
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Protein Structure Ranking with Atom-level Geometric Representation Learning
Tian Xia · Sarp Aykent
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Poster
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[Re] Learning Unknown from Correlations: Graph Neural Network for Inter-novel-protein Interaction Prediction
Urša Zrimšek
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Workshop
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Masked inverse folding with sequence transfer for protein representation learning
Kevin Yang · Niccoló Zanichelli · Hugh Yeh
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Workshop
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Lightweight Equivariant Graph Representation Learning for Protein Engineering
Bingxin Zhou · · Kai Yi · Xinye Xiong · Pan Tan · Liang Hong · Yuguang Wang
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Poster
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TANKBind: Trigonometry-Aware Neural NetworKs for Drug-Protein Binding Structure Prediction
Wei Lu · Qifeng Wu · Jixian Zhang · Jiahua Rao · Chengtao Li · Shuangjia Zheng
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Workshop
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Pretrained protein language model transfer learning: is the final layer representation what we want?
Francesca-Zhoufan Li · Ava Soleimany · Kevin Yang · Alex X Lu
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Workshop
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Standards, tooling and benchmarks to probe representation learning on proteins
Joaquin Gomez Sanchez · Sebastian Franz · Michael Heinzinger · Burkhard Rost · Christian Dallago
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Poster
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Tue 14:00
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Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks
Arian Jamasb · Ramon Viñas Torné · Eric Ma · Yuanqi Du · Charles Harris · Kexin Huang · Dominic Hall · Pietro Lió · Tom Blundell
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Workshop
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Automated Protein Function Description for Novel Class Discovery
Meet Barot · Vladimir Gligorijevic · Richard Bonneau · Kyunghyun Cho
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Workshop
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Conditional Invariances for Conformer Invariant Protein Representations
Balasubramaniam Srinivasan · Vassilis Ioannidis · Soji Adeshina · Mayank Kakodkar · George Karypis · Bruno Ribeiro
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Workshop
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DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Gabriele Corso · Hannes Stärk · Bowen Jing · Regina Barzilay · Tommi Jaakkola
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