75 citations · 133 across the 3 of their papers we have counts for
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q-bio.BM2022★ 55 cited
Generative power of a protein language model trained on multiple sequence alignments
Damiano Sgarbossa, Umberto Lupo, Anne-Florence Bitbol
Computational models starting from large ensembles of evolutionarily related protein sequences capture a representation of protein families and learn constraints associated to prot…
q-bio.BM2022★ 75 cited
Protein language models trained on multiple sequence alignments learn phylogenetic relationships
Umberto Lupo, Damiano Sgarbossa, Anne-Florence Bitbol
Self-supervised neural language models with attention have recently been applied to biological sequence data, advancing structure, function and mutational effect prediction. Some p…