ArticleFrontiers in bioinformatics2022
16S-ITGDB: An Integrated Database for Improving Species Classification of Prokaryotic 16S Ribosomal RNA Sequences.
Article in Frontiers in bioinformatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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20 citing papers in PubMed, 35 citations in OpenAlex.
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- Evaluating Sequencing Strategies for Endometrial Microbiome Profiling in Endometrial Cancer: A Comparative Study of Short- and Long-Read 16S rRNA Approaches.Cancer reports (Hoboken, N.J.) · 2026Article
- Reducing the weaning impact in piglets with dietary fiber: the role of milled almond shells compared to wheat bran.Journal of animal science · 2026Article
- Almond shells as a sustainable alternative to commercial insoluble fiber sources in piglets: effects on performance and digestive health.Journal of animal science · 2026Article
- Bridging taxonomic gaps in microbial community profiling with LSTM-generated synthetic full-length 16S rRNA sequences.ISME communications · 2026Article
- Impact of nursery-to-fattening dietary transitions on gut microbiome composition and growth performance in black soldier fly larvae.Frontiers in microbiology · 2026Article
- NaMeco - Nanopore full-length 16S rRNA gene reads clustering and annotation.BMC genomics · 2025Article
- Distinct gut microbiota profiles and network properties in older Korean individuals with subjective cognitive decline, mild cognitive impairment, and Alzheimer's disease.Alzheimer's research & therapy · 2025Article
- Brain age mediates gut microbiome dysbiosis-related cognition in older adults.Alzheimer's research & therapy · 2025Article
- SpeSpeNet: an interactive and user-friendly tool to create and explore microbial correlation networks.ISME communications · 2025Article
- Peri-implant diseases triggered by oral microdysbiosis: pathogenesis and precision intervention strategies.Frontiers in microbiology · 2025Review
- Saliva microbiome profiling by full-gene 16S rRNA Oxford Nanopore Technology versus Illumina MiSeq sequencing.NPJ biofilms and microbiomes · 2024Article
- Fire-associated microbial shifts in soils of western conifer forests with Armillaria root disease.Applied and environmental microbiology · 2024Article
- Revisiting Socransky's Complexes: A Review Suggesting Updated New Bacterial Clusters (GF-MoR Complexes) for Periodontal and Peri-Implant Diseases and Conditions.Microorganisms · 2024Review
- Microbial dynamics and vertical transmission of Escherichia coli across consecutive life stages of the black soldier fly (Hermetia illucens).Animal microbiome · 2024Article
- GSR-DB: a manually curated and optimized taxonomical database for 16S rRNA amplicon analysis.mSystems · 2024Article
- Evaluation of 16S rRNA genes sequences and genome-based analysis for identification of non-pathogenicFrontiers in microbiology · 2024Article
- SpecGMM: Integrating Spectral analysis and Gaussian Mixture Models for taxonomic classification and identification of discriminative DNA regions.Bioinformatics advances · 2024Article
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Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Analyzing 16S ribosomal RNA (rRNA) sequences allows researchers to elucidate the prokaryotic composition of an environment. In recent years, third-generation sequencing technology has provided opportunities for researchers to perform full-length sequence analysis of bacterial 16S rRNA. RDP, SILVA, and Greengenes are the most widely used 16S rRNA databases. Many 16S rRNA classifiers have used these databases as a reference for taxonomic assignment tasks. However, some of the prokaryotic taxonomies only exist in one of the three databases. Furthermore, Greengenes and SILVA include a considerable number of taxonomies that do not have the resolution to the species level, which has limited the classifiers' performance. In order to improve the accuracy of taxonomic assignment at the species level for full-length 16S rRNA sequences, we manually curated the three databases and removed the sequences that did not have a species name. We then established a taxonomy-based integrated database by considering both taxonomies and sequences from all three 16S rRNA databases and validated it by a mock community. Results showed that our taxonomy-based integrated database had improved taxonomic resolution to the species level. The integrated database and the related datasets are available at https://github.com/yphsieh/ItgDB.
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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.