Abstract

Abstract Microbial systematics is heavily influenced by genome-based methods and challenged by an ever increasing number of taxon names and associated sequences in public data repositories. This poses a challenge for database systems, particularly since it is obviously advantageous if such data are based on a globally recognized approach to manage names, such as the International Code of Nomenclature of Prokaryotes. The amount of data can only be handled if accurate and reliable high-throughput platforms are available that are able to both comply with this demand and to keep track of all changes in an efficient and flexible way. The List of Prokaryotic names with Standing in Nomenclature (LPSN) is an expert-curated authoritative resource for prokaryotic nomenclature and is available at https://lpsn.dsmz.de. The Type (Strain) Genome Server (TYGS) is a high-throughput platform for accurate genome-based taxonomy and is available at https://tygs.dsmz.de. We here present important updates of these two previously introduced, heavily interconnected platforms for taxonomic nomenclature and classification, including new high-level facilities providing access to bioinformatic algorithms, a considerable expansion of the database content, and new ways to easily access the data.

Keywords

BiologyNomenclatureGenomeComputational biologyGeneticsDatabaseTaxonomy (biology)GeneZoologyComputer science

MeSH Terms

AlgorithmsComputational BiologyDatabasesGeneticHumansInternetProkaryotic CellsSoftwareTerminology as Topic

Affiliated Institutions

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Publication Info

Year
2021
Type
article
Volume
50
Issue
D1
Pages
D801-D807
Citations
1766
Access
Closed

Social Impact

Social media, news, blog, policy document mentions

Citation Metrics

1766
OpenAlex
105
Influential
1660
CrossRef

Cite This

Jan P. Meier‐Kolthoff, J. Sarda Carbasse, Rosa L Peinado-Olarte et al. (2021). TYGS and LPSN: a database tandem for fast and reliable genome-based classification and nomenclature of prokaryotes. Nucleic Acids Research , 50 (D1) , D801-D807. https://doi.org/10.1093/nar/gkab902

Identifiers

DOI
10.1093/nar/gkab902
PMID
34634793
PMCID
PMC8728197

Data Quality

Data completeness: 90%