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Status: Unchecked ×Keyword: single amino acid variants ×Clear all

2 claims from 1 paper

1. Biochemistry, Genetics and Molecular Biology › Machine Learning in Bioinformatics

   Embeddings from protein language models predict conservation and variant effects

   Marquet, Heinzinger, Olenyi et al. · Human Genetics · 2021

   The authors used protein language model embeddings to predict conservation and the effects of single amino acid variants without alignments, reporting results competitive with state-of-the-art methods that use alignments.

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   1. UncheckedProtein language model embeddings predicted residue conservation from single sequences almost as well as ConSeq, which uses sequence alignments (MCC 0.596 vs 0.608).“Embeddings alone predicted residue conservation almost as accurately from single sequences as ConSeq using MSAs (two-state Matthews Correlation Coefficient—MCC—for ProtT5 embeddings of 0.596 ± 0.006 vs. 0.608 ± 0.006 for ConSeq).”
   2. UncheckedThe authors' method predicted the effects of single amino acid changes across the whole human proteome (~20,000 proteins) in 40 minutes on one GPU.“Our method predicted SAV effects for the entire human proteome (~ 20 k proteins) within 40 min on one Nvidia Quadro RTX 8000.”