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YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia

Overview of attention for article published in BMC Bioinformatics, January 2015
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (92nd percentile)

Mentioned by

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1 blog
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4 X users
wikipedia
3 Wikipedia pages

Citations

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10 Dimensions

Readers on

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53 Mendeley
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Title
YersiniaBase: a genomic resource and analysis platform for comparative analysis of Yersinia
Published in
BMC Bioinformatics, January 2015
DOI 10.1186/s12859-014-0422-y
Pubmed ID
Authors

Shi Yang Tan, Avirup Dutta, Nicholas S Jakubovics, Mia Yang Ang, Cheuk Chuen Siow, Naresh VR Mutha, Hamed Heydari, Wei Yee Wee, Guat Jah Wong, Siew Woh Choo

Abstract

Background Yersinia is a Gram-negative bacteria that includes serious pathogens such as the Yersinia pestis, which causing plague, Yersinia pseudotuberculosis, Yersinia enterocolitica. The remaining species are generally considered non-pathogenic to humans, although there is evidence that at least some of these species can cause occasional infections using distinct mechanisms from the more pathogenic species. With the advances in sequencing technologies, many genomes of Yersinia have been sequenced. However, there is currently no specialized platform to hold the rapidly-growing Yersinia genomic data and to provide analysis tools particularly for comparative analyses, which are required to provide improved insights into their biology, evolution and pathogenicity.DescriptionTo facilitate the ongoing and future research of Yersinia, especially those generally considered non-pathogenic species, a well-defined repository and analysis platform is needed to hold the Yersinia genomic data and analysis tools for the Yersinia research community. Hence, we have developed the YersiniaBase, a robust and user-friendly Yersinia resource and analysis platform for the analysis of Yersinia genomic data. YersiniaBase has a total of twelve species and 232 genome sequences, of which the majority are Yersinia pestis. In order to smooth the process of searching genomic data in a large database, we implemented an Asynchronous JavaScript and XML (AJAX)-based real-time searching system in YersiniaBase. Besides incorporating existing tools, which include JavaScript-based genome browser (JBrowse) and Basic Local Alignment Search Tool (BLAST), YersiniaBase also has in-house developed tools: (1) Pairwise Genome Comparison tool (PGC) for comparing two user-selected genomes; (2) Pathogenomics Profiling Tool (PathoProT) for comparative pathogenomics analysis of Yersinia genomes; (3) YersiniaTree for constructing phylogenetic tree of Yersinia. We ran analyses based on the tools and genomic data in YersiniaBase and the preliminary results showed differences in virulence genes found in Yersinia pestis and Yersinia pseudotuberculosis compared to other Yersinia species, and differences between Yersinia enterocolitica subsp. enterocolitica and Yersinia enterocolitica subsp. palearctica.ConclusionsYersiniaBase offers free access to wide range of genomic data and analysis tools for the analysis of Yersinia. YersiniaBase can be access at http://yersinia.um.edu.my.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 53 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 23%
Researcher 12 23%
Student > Bachelor 5 9%
Student > Master 4 8%
Professor 3 6%
Other 8 15%
Unknown 9 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 23%
Biochemistry, Genetics and Molecular Biology 10 19%
Immunology and Microbiology 6 11%
Computer Science 6 11%
Veterinary Science and Veterinary Medicine 2 4%
Other 5 9%
Unknown 12 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 April 2022.
All research outputs
#2,163,968
of 22,778,347 outputs
Outputs from BMC Bioinformatics
#585
of 7,276 outputs
Outputs of similar age
#32,601
of 352,360 outputs
Outputs of similar age from BMC Bioinformatics
#10
of 146 outputs
Altmetric has tracked 22,778,347 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,276 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has done particularly well, scoring higher than 91% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 352,360 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.