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The paper presents Spectral Feedback, an algorithm that enhances test-time alignment for discrete diffusion models in protein inverse folding by iteratively selecting edit-positions using sparse Fourier representations, resulting in improved performance for reward maximization.
AlphaGenome Atlas is an AI model that predicts the impact of all 9 billion possible single-letter DNA variants to aid in understanding human biology and disease.
The article discusses a potential strategy to prevent protein misfolding by inhibiting the folding process itself, which could have implications for diseases related to misfolded proteins.
Introduces PairSAE, a method that adapts sparse autoencoders to interpret pairwise representations in protein co-folding models, enabling the discovery of interpretable features that align with biological annotations and predict binding affinities.
Introduces AIMS-Fold, an inference-time guided-diffusion framework that integrates cross-linking mass spectrometry (XL-MS) and hydrogen-deuterium exchange (HDX-MS) data to improve protein co-folding predictions for induced proximity drug targets.
GPT-5.5 autonomously spent over 150 hours improving protein folding models, showcasing advanced AI-driven scientific research.
This article profiles researcher Brian Hie, highlighting how his unique background in literature and computer science informed the development of ESM, a BERT-like model for protein sequences.