ArticleFrontiers in microbiology2021
Beating Naive Bayes at Taxonomic Classification of 16S rRNA Gene Sequences.
Article in Frontiers in microbiology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
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18 citing papers in PubMed.
- Article
- Enhanced identification of key bacterial motility genes via a cross-species genomic hybrid feature machine learning approach.BMC genomics · 2026Article
- Performance and Limitations of Out-Of-Distribution Detection for Insect DNA Barcoding.Ecology and evolution · 2026Article
- Metagenomic insights into microbial community alterations and co-occurrence networks in infective endocarditis.Genomics & informatics · 2025Article
- A Comprehensive Evaluation of Taxonomic Classifiers in Marine Vertebrate eDNA Studies.Molecular ecology resources · 2025Article
- Metagenomic insights into microbial diversity and potential pathogenic transmission in poultry farm environments of Bangladesh.BMC microbiology · 2025Article
- Integrating sequence composition information into microbial diversity analyses with k-mer frequency counting.mSystems · 2025Article
- Review
- The Naïve Bayes classifier++ for metagenomic taxonomic classification-query evaluation.Bioinformatics (Oxford, England) · 2024Article
- Naïve Bayes Classifiers and accompanying dataset for Pseudomonas syringae isolate characterization.Scientific data · 2024Article
- PC-mer: An Ultra-fast memory-efficient tool for metagenomics profiling and classification.PloS one · 2024Article
- Research progress on machine algorithm prediction of liver cancer prognosis after intervention therapy.American journal of cancer research · 2024Review
- Community assembly of the human piercing microbiome.Proceedings. Biological sciences · 2023Article
- Evaluation of a decided sample size in machine learning applications.BMC bioinformatics · 2023Article
- Gut microbiome variation in pulmonary TB patients with diabetes or HIV comorbidities.Frontiers in microbiomes · 2023Article
- An independent evaluation in a CRC patient cohort of microbiome 16S rRNA sequence analysis methods: OTU clustering, DADA2, and Deblur.Frontiers in microbiology · 2023Article
- Robust Classification Using Posterior Probability Threshold Computation Followed by Voronoi Cell Based Class Assignment Circumventing Pitfalls of Bayesian Analysis of Biomedical Data.International journal of molecular sciences · 2022Article
- Increasing transparency and reproducibility in stroke-microbiota research: A toolbox for microbiota analysis.iScience · 2022Article
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4 authors.
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Abstract
Naive Bayes classifiers (NBC) have dominated the field of taxonomic classification of amplicon sequences for over a decade. Apart from having runtime requirements that allow them to be trained and used on modest laptops, they have persistently provided class-topping classification accuracy. In this work we compare NBC with random forest classifiers, neural network classifiers, and a perfect classifier that can only fail when different species have identical sequences, and find that in some practical scenarios there is little scope for improving on NBC for taxonomic classification of 16S rRNA gene sequences. Further improvements in taxonomy classification are unlikely to come from novel algorithms alone, and will need to leverage other technological innovations, such as ecological frequency information.
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