ArticleBioinformatics (Oxford, England)2012
EFICAz2.5: application of a high-precision enzyme function predictor to 396 proteomes.
Article in Bioinformatics (Oxford, England), 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers.
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Who cites it
44 citing papers in PubMed.
- Accurate proteome-wide prediction of enzymes and catalytic sites using graph deep learning and protein language model.GigaScience · 2026Article
- SProtFP: a machine learning-based method for functional classification of small ORFs in prokaryotes.NAR genomics and bioinformatics · 2025Article
- Comparative Assessment of Protein Large Language Models for Enzyme Commission Number Prediction.BMC bioinformatics · 2025Article
- Accurately predicting enzyme functions through geometric graph learning on ESMFold-predicted structures.Nature communications · 2024Article
- Machine Learning and Deep Learning in Synthetic Biology: Key Architectures, Applications, and Challenges.ACS omega · 2024Review
- PredictEFC: a fast and efficient multi-label classifier for predicting enzyme family classes.BMC bioinformatics · 2024Article
- Machine Learning-Guided Protein Engineering.ACS catalysis · 2023Review
- Predicting enzymatic function of protein sequences with attention.Bioinformatics (Oxford, England) · 2023Article
- MAHOMES II: A webserver for predicting if a metal binding site is enzymatic.Protein science : a publication of the Protein Society · 2023Article
- MAHOMES II: A webserver for predicting if a metal binding site is enzymatic.bioRxiv : the preprint server for biology · 2023Article
- Synthetic Biology Meets Machine Learning.Methods in molecular biology (Clifton, N.J.) · 2023Article
- Improving automatic GO annotation with semantic similarity.BMC bioinformatics · 2022Article
- Effects of Sequence Features on Machine-Learned Enzyme Classification Fidelity.Biochemical engineering journal · 2022Article
- Architect: A tool for aiding the reconstruction of high-quality metabolic models through improved enzyme annotation.PLoS computational biology · 2022Article
- PPVED: A machine learning tool for predicting the effect of single amino acid substitution on protein function in plants.Plant biotechnology journal · 2022Article
- Integration of Aspergillus niger transcriptomic profile with metabolic model identifies potential targets to optimise citric acid production from lignocellulosic hydrolysate.Biotechnology for biofuels and bioproducts · 2022Article
- BENZ WS: the Bologna ENZyme Web Server for four-level EC number annotation.Nucleic acids research · 2021Article
- Machine learning differentiates enzymatic and non-enzymatic metals in proteins.Nature communications · 2021Article
- Machine learning for enzyme engineering, selection and design.Protein engineering, design & selection : PEDS · 2021Review
- Predicting metabolic pathways of plant enzymes without using sequence similarity: Models from machine learning.The plant genome · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
unlabelledHigh-quality enzyme function annotation is essential for understanding the biochemistry, metabolism and disease processes of organisms. Previously, we developed a multi-component high-precision enzyme function predictor, EFICAz(2) (enzyme function inference by a combined approach). Here, we present an updated improved version, EFICAz(2.5), that is trained on a significantly larger data set of enzyme sequences and PROSITE patterns. We also present the results of the application of EFICAz(2.5) to the enzyme reannotation of 396 genomes cataloged in the ENSEMBL database. AVAILABILITY: The EFICAz(2.5) server and database is freely available with a use-friendly interface at http://cssb.biology.gatech.edu/EFICAz2.5.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.