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Neo-1 Decode & Design the Structures of Life

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Proteina Scaling Flow-based Protein Structure Generative Models Karsten Kreis and Tomas Geffner

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Emulation of protein equilibrium ensembles with generative deep learning José Jiménez Luna, Yu Xie

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Boltz-1 Democratizing Biomolecular Interaction Modeling Jeremy Wohlwend, Gabriele Corso

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Generative modeling of molecular dynamics trajectories Bowen Jing and Hannes Stärk

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Feedback and next steps

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PLINDER session

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Connected concepts in datasets

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Intro to dataset presentations

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Metrics for measuring protein and complex model accuracy

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Welcome and introduction

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PINDER dataset for PPI prediction

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Hugging Face models and leaderboard submission

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P(L)INDER New benchmarks for molecular interactions Zhonglin Cao, Jay Durairaj, Danny Kovtun

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FoldFlow-2 Flow Matching For Protein Backbone Generation Guillaume Huguet, James Vuckovic

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Metric Flow Matching Kacper Kapusniak, Francesco Di Giovanni

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Deep Confident Steps to New Pockets Strategies for Docking Generalization Gabriele Corso

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Evo DNA foundation modeling from molecular to genome scale Brian Hie

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Generative Flows on Discrete State-Spaces Andrew Campbell, Jason Yim

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SE(3)-Stochastic Flow Matching for Protein Backbone Generation Joey Bose, Alex Tong

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Illuminating protein space with a programmable generative model Gevorg Grigoryan, Zak Costello

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Flow Matching Simplifying and Generalizing Diffusion Models Yaron Lipman

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Evaluating AI models for structure-based drug design Charlie Harris, Martin Buttenschoen

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Harnessing Geometry For Molecular Design Michael Bronstein, Bruno Correia

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