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Found 3 papers, 1 papers with code
Transformer protein language models are unsupervised structure learners
Unsupervised contact prediction is central to uncovering physical, structural, and functional constraints for protein structure determination and design.
Single Layers of Attention Suffice to Predict Protein Contacts
On the one hand, factored attention is a direct simplification of multihead scaled dot-product attention in the Transformer.
Unified framework for modeling multivariate distributions in biological sequences
Revealing the functional sites of biological sequences, such as evolutionary conserved, structurally interacting or co-evolving protein sites, is a fundamental, and yet challenging task.
Quantitative Methods
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