Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies

Introducing EzBioCloud: a taxonomically united database of 16S rRNA gene sequences and whole-genome assemblies

2017 | Seok-Hwan Yoon, Sung-Min Ha, Soonjae Kwon, Jeongmin Lim, Yeseul Kim, Hyungseok Seo and Jongsik Chun
The article introduces EzBioCloud, an integrated database that combines taxonomic information with 16S rRNA gene sequences and whole-genome assemblies of *Bacteria* and *Archaea*. The database aims to enhance the classification and identification of prokaryotic species by providing a comprehensive taxonomic hierarchy. It includes 61,700 species/phylogroups and 62,362 whole-genome assemblies, identified at the genus, species, and subspecies levels. The database uses a composite bioinformatics pipeline that combines gene-based searches and average nucleotide identity (ANI) calculations to ensure accurate taxonomic assignments. Additionally, it provides genomic properties such as genome size, DNA G+C content, and occurrence in human microbiome data. The database and its search tools are accessible at www.ezbiocloud.net/ and are expected to accelerate genome-based classification and identification in microbiology.The article introduces EzBioCloud, an integrated database that combines taxonomic information with 16S rRNA gene sequences and whole-genome assemblies of *Bacteria* and *Archaea*. The database aims to enhance the classification and identification of prokaryotic species by providing a comprehensive taxonomic hierarchy. It includes 61,700 species/phylogroups and 62,362 whole-genome assemblies, identified at the genus, species, and subspecies levels. The database uses a composite bioinformatics pipeline that combines gene-based searches and average nucleotide identity (ANI) calculations to ensure accurate taxonomic assignments. Additionally, it provides genomic properties such as genome size, DNA G+C content, and occurrence in human microbiome data. The database and its search tools are accessible at www.ezbiocloud.net/ and are expected to accelerate genome-based classification and identification in microbiology.
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