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File: S41467 022 34032 Y
Article https://doi.org/10.1038/s41467-022-34032-y Proteinlanguagemodelstrainedonmultiple sequence alignments learn phylogenetic relationships Received: 8 April 2022 UmbertoLupo 1,2 , Damiano Sgarbossa 1,2 & Anne-Florence Bitbol 1,2 Accepted: 7 October ...

icon picture PDF Filetype PDF | Posted on 01 Feb 2023 | 2 years ago

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...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...
								

							

						
	
												
				
					
					
					
			
					
				
				
		
	

	
		





	

	
				

						

						
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Posted on: 01 Feb 2023 | 2 years ago
										
										
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