ArticleiScience2025
Annotating the microbial dark matter with HiFi-NN.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- WASP: a pipeline for functional annotation prediction based on AlphaFold structural models.Nature communications · 2026Article
- Integrating Protein Language Models with Multimodal Embeddings to Accelerate Function Prediction of Uncharacterized Proteins.International journal of molecular sciences · 2026Review
- EC-Bench: a benchmark for enzyme commission number prediction.Bioinformatics advances · 2026Article
- ProtNote: a multimodal method for protein-function annotation.Bioinformatics (Oxford, England) · 2025Article
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Authors and funding
7 authors.
Funding
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Abstract
The accurate computational annotation of protein sequences with enzymatic function remains a fundamental challenge in bioinformatics. Here, we present HiFi-NN (Hierarchically-Finetuned Nearest Neighbor search) which annotates protein sequences to the 4th level of Enzyme Commission (EC) number with greater precision and recall than state-of-the-art deep learning methods. Furthermore, we show that this method can correctly identify the EC number of a given sequence to lower identities than BLASTp. We show that performance can be improved by increasing the diversity of the lookup set in both sequence space and the environment the sequence has been sampled from. We proceed to show that we can correct specific mis-annotations in the BRENDA enzymes database reproducing results found by others. Finally, we use HiFi-NN to annotate functional dark-matter protein sequences from NMPFamDB. Our findings pave the way for more accurate functional annotation
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Registered trials
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