1 - 19 of 19 results

LPSN / List of Prokaryotic Names with Standing in Nomenclature

Gathers the names of prokaryotes (Bacteria and Archaea) published in the International Journal of Systematic and Evolutionary Microbiology (IJSEM) directly or by inclusion in a Validation List, under the Rules of International Code of Nomenclature of Bacteria. LPSN provides information about the current status of a name and its synonyms. The classification is based on (i) the original publications, and/or the latest “Taxonomic Outline of the Bacteria and Archaea”, (ii) and/or the “NCBI Taxonomy Browser” and/or (iii) “The All-Species Living Tree Project”.

MicroTaxi / Microbial Taxonomic Identification

A comprehensive method which uses the taxon-specific genes for the correct taxonomic assignment of existing and new bacterial genomes. MicroTaxi provides an alternate valuable methodology to carry out the taxonomic classification of newly sequenced or existing bacterial genomes. The taxon-specific genes identified at each taxonomic rank have been successfully used for the taxonomic classification of 2,342 genomes present in the NCBI genomes, 36 newly sequenced genomes, and 17 genomes for which the complete taxonomy is not yet known.

SISTR / Salmonella In Silico Typing Resource

A bioinformatics platform for rapidly performing simultaneous in silico analyses for several leading subtyping methods on draft Salmonella genome assemblies. In addition to performing serovar prediction by genoserotyping, SISTR integrates sequence-based typing analyses for: Multi-Locus Sequence Typing (MLST), ribosomal MLST (rMLST), and core genome MLST (cgMLST). We show how phylogenetic context from cgMLST analysis can supplement the genoserotyping analysis and increase the accuracy of in silico serovar prediction to over 94.6% on a dataset comprised of 4,188 finished genomes and WGS draft assemblies. In addition to allowing analysis of user-uploaded whole-genome assemblies, the SISTR platform incorporates a database comprising over 4,000 publicly available genomes, allowing users to place their isolates in a broader phylogenetic and epidemiological context. The resource incorporates several metadata driven visualizations to examine the phylogenetic, geospatial and temporal distribution of genome-sequenced isolates.

CETAF Stable Identifiers

Follows Linked Open Data principles and implements redirection mechanisms to human-readable and machine-readable representations of specimens facilitating seamless integration into the growing semantic web. The CETAF Stable Identifiers is a common system of HTTP-URI-based stable identifiers. It increasingly used for referencing specimens in taxonomic publications, data portals, and web service interfaces. In addition, several pilot projects are underway to demonstrate the integration into Linked Open Data based applications.

BioMaS / Bioinformatic analysis of Metagenomic AmpliconS

A bioinformatic pipeline designed to support biomolecular researchers involved in taxonomic studies of environmental microbial communities. BioMaS uses completely automated workflow, comprehensive of all the fundamental steps, from raw sequence data upload and cleaning to final taxonomic identification, that are absolutely required in an appropriately designed Meta-barcoding High-Throughput Sequencing (HTS)-based experiment. It allows the analysis of both bacterial and fungal environments starting directly from the raw sequencing data from either Roche 454 or Illumina HTS platforms, following two alternative paths, respectively. BioMaS outperforms QIIME and MOTHUR in terms of extent and accuracy of deep taxonomic sequence assignments.


Performs predictions for draft or complete genomes but not for short reads. TaxonomyFinder is based on species-specific functional protein domain profiles. The workflow of this method is a four-step process, as follows: (i) the open reading frame (ORF) is predicted using Prodigal, (ii) functional profiles are constructed from protein coding sequences, (iii) functional profiles are assigned, and (iv) functional profiles are compared to the taxonomy-specific profile database.