The World Bacterial Biogeography and Biodiversity through Databases: A Case Study of NCBI Nucleotide Database and GBIF Database

Databases are an essential tool and resource within the field of bioinformatics. The primary aim of this study was to generate an overview of global bacterial biodiversity and biogeography using available data from the two largest public online databases, NCBI Nucleotide and GBIF. The secondary aim...

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Bibliographic Details
Published in:BioMed Research International
Main Authors: Selama, Okba, James, Phillip, Nateche, Farida, Wellington, Elizabeth M. H., Hacène, Hocine
Format: Text
Language:English
Published: Hindawi Publishing Corporation 2013
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Online Access:http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3818805
https://doi.org/10.1155/2013/240175
Description
Summary:Databases are an essential tool and resource within the field of bioinformatics. The primary aim of this study was to generate an overview of global bacterial biodiversity and biogeography using available data from the two largest public online databases, NCBI Nucleotide and GBIF. The secondary aim was to highlight the contribution each geographic area has to each database. The basis for data analysis of this study was the metadata provided by both databases, mainly, the taxonomy and the geographical area origin of isolation of the microorganism (record). These were directly obtained from GBIF through the online interface, while E-utilities and Python were used in combination with a programmatic web service access to obtain data from the NCBI Nucleotide Database. Results indicate that the American continent, and more specifically the USA, is the top contributor, while Africa and Antarctica are less well represented. This highlights the imbalance of exploration within these areas rather than any reduction in biodiversity. This study describes a novel approach to generating global scale patterns of bacterial biodiversity and biogeography and indicates that the Proteobacteria are the most abundant and widely distributed phylum within both databases.