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Using average nucleotide identity to improve taxonomic assignments in prokaryotic genomes at the NCBI
INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · 2018 · Vol. 68(7) · pp. 2386–2392
Stacy Ciufo✉(National Center for Biotechnology Information)Sivakumar Kannan(National Center for Biotechnology Information)Shobha Sharma(National Center for Biotechnology Information)Azat Badretdin(National Center for Biotechnology Information)Karen Clark(National Institutes of Health)Seán Turner(National Institutes of Health)Vyacheslav Brover(National Institutes of Health)Conrad L. Schoch(National Institutes of Health)Avi Kimchi(National Center for Biotechnology Information)Michael DiCuccio(National Institutes of Health)
Abstract
Average nucleotide identity analysis is a useful tool to verify taxonomic identities in prokaryotic genomes, for both complete and draft assemblies. Using optimum threshold ranges appropriate for different prokaryotic taxa, we have reviewed all prokaryotic genome assemblies in GenBank with regard to their taxonomic identity. We present the methods used to make such comparisons, the current status of GenBank verifications, and recent developments in confirming species assignments in new genome submissions.
Genomics and Phylogenetic StudiesIdentification and Quantification in FoodRNA and protein synthesis mechanismsGenBankBiologyGenomeTaxonIdentity (music)Taxonomic rankBiological classificationComputational biologyGeneticsEvolutionary biology
MeSH terms
Base CompositionNucleotidesPhylogenyProkaryotic CellsGenome, BacterialSequence Analysis, DNAGenome, ArchaealDatabases, Nucleic Acid
Funding
- National Institutes of Health
- U.S. National Library of Medicine
Citations
506
FWCI
16.15
field-weighted impact
References
20
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100%
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Citations per year
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References
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Proceedings of the National Academy of Sciences · 2009 · 6,211 citations
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INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · 2014 · 3,054 citations
International Code of Nomenclature of Prokaryotes
INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · 2015 · 720 citations
Mash: fast genome and metagenome distance estimation using MinHash
Genome biology · 2016 · 3,435 citations
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