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Comparative functional pan-genome analyses to build connections between genomic dynamics and phenotypic evolution in polycyclic aromatic hydrocarbon metabolism in the genus Mycobacterium

Overview of attention for article published in BMC Ecology and Evolution, February 2015
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Title
Comparative functional pan-genome analyses to build connections between genomic dynamics and phenotypic evolution in polycyclic aromatic hydrocarbon metabolism in the genus Mycobacterium
Published in
BMC Ecology and Evolution, February 2015
DOI 10.1186/s12862-015-0302-8
Pubmed ID
Authors

Ohgew Kweon, Seong-Jae Kim, Jochen Blom, Sung-Kwan Kim, Bong-Soo Kim, Dong-Heon Baek, Su Inn Park, John B Sutherland, Carl E Cerniglia

Abstract

The bacterial genus Mycobacterium is of great interest in the medical and biotechnological fields. Despite a flood of genome sequencing and functional genomics data, significant gaps in knowledge between genome and phenome seriously hinder efforts toward the treatment of mycobacterial diseases and practical biotechnological applications. In this study, we propose the use of systematic, comparative functional pan-genomic analysis to build connections between genomic dynamics and phenotypic evolution in polycyclic aromatic hydrocarbon (PAH) metabolism in the genus Mycobacterium.

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X Demographics

The data shown below were collected from the profile of 1 X user 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 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
France 1 1%
Brazil 1 1%
Unknown 72 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 17 23%
Student > Master 9 12%
Researcher 9 12%
Student > Doctoral Student 7 9%
Student > Bachelor 7 9%
Other 8 11%
Unknown 18 24%
Readers by discipline Count As %
Agricultural and Biological Sciences 19 25%
Biochemistry, Genetics and Molecular Biology 11 15%
Computer Science 4 5%
Medicine and Dentistry 4 5%
Immunology and Microbiology 4 5%
Other 15 20%
Unknown 18 24%
Attention Score in Context

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 17 April 2015.
All research outputs
#19,512,854
of 24,003,070 outputs
Outputs from BMC Ecology and Evolution
#2,595
of 2,908 outputs
Outputs of similar age
#270,923
of 366,502 outputs
Outputs of similar age from BMC Ecology and Evolution
#48
of 54 outputs
Altmetric has tracked 24,003,070 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,908 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one is in the 4th percentile – i.e., 4% 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 366,502 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 54 others from the same source and published within six weeks on either side of this one. This one is in the 7th percentile – i.e., 7% of its contemporaries scored the same or lower than it.