TriProRep learns structure-aware protein representations via three-view VQ-VAE pretraining and shows gains on the new RepSP benchmark for dimer co-folding, interaction properties, and monomer structure prediction.
Masked inverse folding with sequence transfer for protein representation learning.Protein Engineering, Design and Selection, 36:gzad015, 2023
2 Pith papers cite this work. Polarity classification is still indexing.
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EvoIF integrates within-family and cross-family evolutionary signals into a compact model to achieve competitive or state-of-the-art zero-shot fitness prediction on ProteinGym using only 0.15% of typical training data.
citing papers explorer
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Atom-level Protein Representation Learning Improves Protein Structure Prediction
TriProRep learns structure-aware protein representations via three-view VQ-VAE pretraining and shows gains on the new RepSP benchmark for dimer co-folding, interaction properties, and monomer structure prediction.
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Evolutionary Profiles for Protein Fitness Prediction
EvoIF integrates within-family and cross-family evolutionary signals into a compact model to achieve competitive or state-of-the-art zero-shot fitness prediction on ProteinGym using only 0.15% of typical training data.