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Deep-learning language models help to improve protein sequence alignment - Nature Methods

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Deep-learning language models help to improve protein sequence alignment - Nature Methods

We trained DEDAL, an algorithm based on deep-learning language models, to generate pairwise alignments of protein sequences taking into account the sequence-specific context of amino acid substitutions or gaps. DEDAL improved the alignment correctness on remote homologs by up to threefold and the discrimination of remote homologs from evolutionarily unrelated sequences.

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Deep-learning language models help to improve protein sequence alignment - Nature Methods

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Deep-learning language models help to improve protein sequence alignment - Nature Methods

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