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Prediction of Type II Toxin-Antitoxin Loci in Klebsiella pneumoniae Genome Sequences

Overview of attention for article published in Interdisciplinary Sciences: Computational Life Sciences, December 2015
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Title
Prediction of Type II Toxin-Antitoxin Loci in Klebsiella pneumoniae Genome Sequences
Published in
Interdisciplinary Sciences: Computational Life Sciences, December 2015
DOI 10.1007/s12539-015-0135-6
Pubmed ID
Authors

Yi-Qing Wei, De-Xi Bi, Dong-Qing Wei, Hong-Yu Ou

Abstract

Klebsiella pneumoniae is an increasingly important bacterial pathogen to human. This Gram-negative bacterium species has become a serious concern due to its dramatic increase in the levels of multiple antibiotic resistances, particularly to carbapenems. The toxin-antitoxin (TA) system has recently been reported to be involved in the formation of drug-tolerant persister cells. The type II TA system is composed of a stable toxin protein and a relatively unstable antitoxin protein that is able to inhibit the toxin. Here, we examine the type II TA locus distribution and compare the TA diversity throughout ten completely sequenced K. pneumoniae genomes by using bioinformatics approaches. Two hundred and twelve putative type II TA loci were identified in 30 replicons of these K. pneumoniae strains. The amino acid sequence similarity-based grouping shows that these loci distribute differently not only among different K. pneumoniae strains isolated from diverse sources, but also between their chromosomes and plasmids.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 1 3%
India 1 3%
Unknown 38 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 10 25%
Researcher 8 20%
Student > Master 5 13%
Student > Bachelor 3 8%
Lecturer 2 5%
Other 4 10%
Unknown 8 20%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 45%
Agricultural and Biological Sciences 5 13%
Immunology and Microbiology 5 13%
Medicine and Dentistry 4 10%
Unknown 8 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 16 December 2015.
All research outputs
#14,830,048
of 22,835,198 outputs
Outputs from Interdisciplinary Sciences: Computational Life Sciences
#97
of 294 outputs
Outputs of similar age
#216,456
of 388,829 outputs
Outputs of similar age from Interdisciplinary Sciences: Computational Life Sciences
#3
of 5 outputs
Altmetric has tracked 22,835,198 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 294 research outputs from this source. They receive a mean Attention Score of 2.9. This one has gotten more attention than average, scoring higher than 62% 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 388,829 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.