ArticleNature communications2025
Empathi: embedding-based phage protein annotation tool by hierarchical assignment.
Article in Nature communications, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Precision phage therapy in the AI/ML era: a systematic review of discovery-to-clinical translation evidence.Frontiers in microbiology · 2026Pooled it
- Phage bioinformatics tools: a review of computational approaches for bacteriophage research.Briefings in bioinformatics · 2026Review
- Computational prediction resolves thousands of homooligomeric phage protein structures.bioRxiv : the preprint server for biology · 2026Article
- The Unified Human Virome Database: A toolkit for expanded human virome analysis.bioRxiv : the preprint server for biology · 2026Article
- PhaLP 2.0: extending the community-oriented phage lysin database with a SUBLYME pipeline for metagenomic discovery.Database : the journal of biological databases and curation · 2026Article
- Protein structure-informed bacteriophage genome annotation with Phold.Nucleic acids research · 2026Article
- Isolation and Characterization of Clostridioides difficile Bacteriophages.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Artificial Intelligence Applications in Bacteriophage Genomics and Host Interaction.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Phage evolutionary relationships emerge from protein language model-based proteome representation.NAR genomics and bioinformatics · 2025Article
- Computational function prediction of bacteria and phage proteins.Microbiology and molecular biology reviews : MMBR · 2025Review
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5 authors.
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Abstract
Bacteriophages, viruses infecting bacteria, are estimated to outnumber their cellular hosts by 10-fold, acting as key players in all microbial ecosystems. Under evolutionary pressure by their host, they evolve rapidly and encode a large diversity of protein sequences. Consequently, the majority of functions carried by phage proteins remain elusive. Current tools to comprehensively identify phage protein functions from their sequence either lack sensitivity (those relying on homology for instance) or specificity (assigning a single coarse grain function to a protein). Here, we introduce Empathi, a protein-embedding-based classifier that assigns functions in a hierarchical manner. New categories were specifically elaborated for phage protein functions and organized such that molecular-level functions are respected in each category, making them well suited for training machine learning classifiers based on protein embeddings. Empathi outperforms homology-based methods on a dataset of cultured phage genomes, tripling the number of annotated homologous groups. On the EnVhogDB database, the most recent and extensive database of metagenomically-sourced phage proteins, Empathi doubled the annotated fraction of protein families from 16% to 33%. Having a more global view of the repertoire of functions a phage possesses will assuredly help to understand them and their interactions with bacteria better.
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