ArticleBioinformatics (Oxford, England)2021
DeepNOG: fast and accurate protein orthologous group assignment.
Article in Bioinformatics (Oxford, England), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers.
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Who cites it
32 citing papers in PubMed.
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- Genomic and experimental characterization of unique Antarctic temperate phage Perkons reveals multiple integrases and complex lysogenic dynamics in Psychrobacillus sp. L4.BMC microbiology · 2026Article
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- B-cell peptide epitopes as diagnostic targets for Q fever in sheep.Frontiers in microbiology · 2026Article
- Description of high-altitude, cold-adaptive, metabolically versatileMicrobiology spectrum · 2025Article
- Feature Architecture-Aware Ortholog Search With fDOG Reveals the Distribution of Plant Cell Wall-Degrading Enzymes Across Life.Molecular biology and evolution · 2025Article
- Review
- The first whole-genome sequence of a prospective novel sponge-associatedF1000Research · 2025Article
- Decoding the anomalies: a genome-based analysis ofFrontiers in microbiology · 2025Article
- Genomic analysis of co-infection withFrontiers in microbiology · 2025Article
- Antimicrobial resistance and genomic characterization ofFrontiers in microbiology · 2025Article
- Protective Potential ofJournal of microbiology and biotechnology · 2024Article
- Microbiota profiling in esophageal diseases: Novel insights into molecular staining and clinical outcomes.Computational and structural biotechnology journal · 2024Review
- Whole Genome Sequence Analysis of Brucella spp. from Human, Livestock, and Wildlife in South Africa.Journal of microbiology (Seoul, Korea) · 2024Article
- Article
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Authors and funding
6 authors.
Funding
Abstract
motivationProtein orthologous group databases are powerful tools for evolutionary analysis, functional annotation or metabolic pathway modeling across lineages. Sequences are typically assigned to orthologous groups with alignment-based methods, such as profile hidden Markov models, which have become a computational bottleneck.
resultsWe present DeepNOG, an extremely fast and accurate, alignment-free orthology assignment method based on deep convolutional networks. We compare DeepNOG against state-of-the-art alignment-based (HMMER, DIAMOND) and alignment-free methods (DeepFam) on two orthology databases (COG, eggNOG 5). DeepNOG can be scaled to large orthology databases like eggNOG, for which it outperforms DeepFam in terms of precision and recall by large margins. While alignment-based methods still provide the most accurate assignments among the investigated methods, computing time of DeepNOG is an order of magnitude lower on CPUs. Optional GPU usage further increases throughput massively. A command-line tool enables rapid adoption by users. AVAILABILITYAND IMPLEMENTATION: Source code and packages are freely available at https://github.com/univieCUBE/deepnog. Install the platform-independent Python program with $pip install deepnog. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.
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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.