ArticleNAR genomics and bioinformatics2022
Contrastive learning on protein embeddings enlightens midnight zone.
Article in NAR genomics and bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 60 papers.
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Who cites it
60 citing papers in PubMed.
- EmmaEmb: A quantitative framework for analyzing embedding spaces in molecular biology.Patterns (New York, N.Y.) · 2026Article
- FANTASIA suite: a reproducible and configurable framework for embedding-based functional annotation of proteins.NAR genomics and bioinformatics · 2026Article
- Contrastive learning unites sequence and structure in a global representation of protein space.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Scaling SMILES-based chemical language models for therapeutic peptide engineering.bioRxiv : the preprint server for biology · 2026Article
- Identifying microbial protease allergens through protein language model-guided homology.Cell systems · 2026Article
- Protein structure-informed bacteriophage genome annotation with Phold.Nucleic acids research · 2026Article
- Evaluating Pretrained Protein Language Model Embeddings as Proxies for Functional Similarity.Journal of molecular evolution · 2025Article
- Protein language models uncover carbohydrate-active enzyme function in metagenomics.BMC bioinformatics · 2025Article
- Evaluating the significance of embedding-based protein sequence alignment with clustering and double dynamic programming for remote homology.Scientific reports · 2025Article
- Zero-shot segmentation using embeddings from a protein language model identifies functional regions in the human proteome.PLoS computational biology · 2025Article
- DeepFold-PLM: accelerating protein structure prediction via efficient homology search using protein language models.Bioinformatics (Oxford, England) · 2025Article
- Computational function prediction of bacteria and phage proteins.Microbiology and molecular biology reviews : MMBR · 2025Review
- SPACE: STRING proteins as complementary embeddings.Bioinformatics (Oxford, England) · 2025Article
- Application of Protein Structure Encodings and Sequence Embeddings for Transporter Substrate Prediction.Molecules (Basel, Switzerland) · 2025Article
- Protein Structural Phylogenetics.Genome biology and evolution · 2025Review
- ConsAMPHemo: A computational framework for predicting hemolysis of antimicrobial peptides based on machine learning approaches.Protein science : a publication of the Protein Society · 2025Article
- GOBeacon: An ensemble model for protein function prediction enhanced by contrastive learning.Protein science : a publication of the Protein Society · 2025Article
- Annotating the microbial dark matter with HiFi-NN.iScience · 2025Article
- Fast, sensitive detection of protein homologs using deep dense retrieval.Nature biotechnology · 2025Article
- Accurate Predictions of Molecular Properties of Proteins via Graph Neural Networks and Transfer Learning.Journal of chemical theory and computation · 2025Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Experimental structures are leveraged through multiple sequence alignments, or more generally through homology-based inference (HBI), facilitating the transfer of information from a protein with known annotation to a query without any annotation. A recent alternative expands the concept of HBI from sequence-distance lookup to embedding-based annotation transfer (EAT). These embeddings are derived from protein Language Models (pLMs). Here, we introduce using single protein representations from pLMs for contrastive learning. This learning procedure creates a new set of embeddings that optimizes constraints captured by hierarchical classifications of protein 3D structures defined by the CATH resource. The approach, dubbed
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