Protein structure prediction from amino acid sequences using self-attention neural networks

Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a predicted structure of a protein that is specified by an amino acid sequence. In one aspect, a method comprises: obtaining a multiple sequence alignment for the protein; determining,...

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Hauptverfasser: Bates, Russell James, Senior, Andrew W, Jumper, John, Figurnov, Mikhail, Pritzel, Alexander, Evans, Richard Andrew, Green, Timothy Frederick Goldie
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creator Bates, Russell James
Senior, Andrew W
Jumper, John
Figurnov, Mikhail
Pritzel, Alexander
Evans, Richard Andrew
Green, Timothy Frederick Goldie
description Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for determining a predicted structure of a protein that is specified by an amino acid sequence. In one aspect, a method comprises: obtaining a multiple sequence alignment for the protein; determining, from the multiple sequence alignment and for each pair of amino acids in the amino acid sequence of the protein, a respective initial embedding of the pair of amino acids; processing the initial embeddings of the pairs of amino acids using a pair embedding neural network comprising a plurality of self-attention neural network layers to generate a final embedding of each pair of amino acids; and determining the predicted structure of the protein based on the final embedding of each pair of amino acids.
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subjects CALCULATING
COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
COMPUTING
COUNTING
INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS
PHYSICS
title Protein structure prediction from amino acid sequences using self-attention neural networks
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