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PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity

Overview of attention for article published in BMC Bioinformatics, March 2012
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  • Above-average Attention Score compared to outputs of the same age and source (51st percentile)

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Citations

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Title
PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity
Published in
BMC Bioinformatics, March 2012
DOI 10.1186/1471-2105-13-37
Pubmed ID
Authors

Bhakti Dwivedi, Robert Schmieder, Dawn B Goldsmith, Robert A Edwards, Mya Breitbart

Abstract

Phages (viruses that infect bacteria) have gained significant attention because of their abundance, diversity and important ecological roles. However, the lack of a universal gene shared by all phages presents a challenge for phage identification and characterization, especially in environmental samples where it is difficult to culture phage-host systems. Homologous conserved genes (or "signature genes") present in groups of closely-related phages can be used to explore phage diversity and define evolutionary relationships amongst these phages. Bioinformatic approaches are needed to identify candidate signature genes and design PCR primers to amplify those genes from environmental samples; however, there is currently no existing computational tool that biologists can use for this purpose.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 138 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Nepal 1 <1%
South Africa 1 <1%
Australia 1 <1%
Mexico 1 <1%
Canada 1 <1%
Unknown 131 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 28 20%
Researcher 28 20%
Student > Master 19 14%
Student > Bachelor 12 9%
Student > Postgraduate 10 7%
Other 26 19%
Unknown 15 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 57 41%
Biochemistry, Genetics and Molecular Biology 24 17%
Immunology and Microbiology 15 11%
Computer Science 5 4%
Environmental Science 4 3%
Other 13 9%
Unknown 20 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 18 August 2012.
All research outputs
#7,412,989
of 22,663,150 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,246 outputs
Outputs of similar age
#51,492
of 156,248 outputs
Outputs of similar age from BMC Bioinformatics
#23
of 60 outputs
Altmetric has tracked 22,663,150 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,246 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 gotten more attention than average, scoring higher than 50% 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 156,248 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 60 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 51% of its contemporaries.