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Inferring bacteriophage infection strategies from genome sequence: analysis of bacteriophage 7-11 and related phages

Overview of attention for article published in BMC Evolutionary Biology, January 2015
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Title
Inferring bacteriophage infection strategies from genome sequence: analysis of bacteriophage 7-11 and related phages
Published in
BMC Evolutionary Biology, January 2015
DOI 10.1186/1471-2148-15-s1-s1
Pubmed ID
Authors

Jelena Guzina, Marko Djordjevic

Abstract

Analyzing regulation of bacteriophage gene expression historically lead to establishing major paradigms of molecular biology, and may provide important medical applications in the future. Temporal regulation of bacteriophage transcription is commonly analyzed through a labor-intensive combination of biochemical and bioinformatic approaches and macroarray measurements. We here investigate to what extent one can understand gene expression strategies of lytic phages, by directly analyzing their genomes through bioinformatic methods. We address this question on a recently sequenced lytic bacteriophage 7 - 11 that infects bacterium Salmonella enterica.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 22%
Student > Master 4 17%
Researcher 4 17%
Unspecified 3 13%
Student > Postgraduate 3 13%
Other 4 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 8 35%
Biochemistry, Genetics and Molecular Biology 8 35%
Unspecified 3 13%
Immunology and Microbiology 2 9%
Computer Science 1 4%
Other 1 4%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 25 February 2015.
All research outputs
#4,022,610
of 4,804,615 outputs
Outputs from BMC Evolutionary Biology
#1,401
of 1,506 outputs
Outputs of similar age
#119,982
of 145,265 outputs
Outputs of similar age from BMC Evolutionary Biology
#42
of 43 outputs
Altmetric has tracked 4,804,615 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,506 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.3. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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 145,265 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.