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Survey of Protein Sequence Embedding Models

14 Feb 2023

Abstract excerpt

Derived from the natural language processing (NLP) algorithms, protein language models enable the encoding of protein sequences, which are widely diverse in length and amino acid composition, in fixed-size numerical vectors (embeddings). We surveyed representative embedding models such as Esm, Esm1b, ProtT5, and SeqVec, along with their derivatives (GoPredSim and PLAST), to conduct the following tasks in...

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PMID: 36835188
DOI: 10.3390/ijms24043775

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