Assessing the role of evolutionary information for enhancing protein language model embeddings

Abstract Embeddings from protein Language Models (pLMs) are replacing evolutionary information from multiple sequence alignments (MSAs) as the most successful input for protein prediction. Is this because embeddings capture evolutionary information? We tested various approaches to explicitly incorpo...

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Bibliographic Details

Published in:	Scientific Reports
Main Authors:	Kyra Erckert, Burkhard Rost
Format:	Article
Language:	English
Published:	Nature Portfolio 2024-09-01
Subjects:	Embeddings Machine learning Evolutionary information Protein language models Multiple sequence alignments Protein structure prediction
Online Access:	https://doi.org/10.1038/s41598-024-71783-8