The words contained in this file might help you see if this file matches what you are looking for:
...Article https doi org s y proteinlanguagemodelstrainedonmultiple sequence alignments learn phylogenetic relationships received april umbertolupo damiano sgarbossa anne florence bitbol accepted october self supervised neural language models with attention have recently been applied to biological data advancing structure function and checkforupdates mutational effect prediction some protein including msa transformer alphafold sevoformer takemultiplesequencealignments msas of evolutionarily related proteins as inputs simple combinations msatransformer row attentions led state the art unsupervised structural contact we demonstrate that similarly uni versal column strongly cor relate hamming distances between sequences in therefore based encode detailed wefurther show these can separate coevolutionary signals encodingfunctionalandstructuralconstraintsfromphylogeneticcorrelations re ecting historical contingency assess this generate synthetic either without or phylogeny from potts trained on...