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Identifying co-targets to fight drug resistance based on a random walk model

Overview of attention for article published in BMC Systems Biology, January 2012
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Citations

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Title
Identifying co-targets to fight drug resistance based on a random walk model
Published in
BMC Systems Biology, January 2012
DOI 10.1186/1752-0509-6-5
Pubmed ID
Authors

Liang-Chun Chen, Hsiang-Yuan Yeh, Cheng-Yu Yeh, Carlos Roberto Arias, Von-Wun Soo

Abstract

Drug resistance has now posed more severe and emergent threats to human health and infectious disease treatment. However, wet-lab approaches alone to counter drug resistance have so far still achieved limited success due to less knowledge about the underlying mechanisms of drug resistance. Our approach apply a heuristic search algorithm in order to extract active network under drug treatment and use a random walk model to identify potential co-targets for effective antibacterial drugs.

X Demographics

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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Zimbabwe 1 1%
Unknown 65 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 24 36%
Researcher 13 19%
Student > Bachelor 6 9%
Professor > Associate Professor 5 7%
Student > Master 5 7%
Other 6 9%
Unknown 8 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 42%
Computer Science 9 13%
Biochemistry, Genetics and Molecular Biology 6 9%
Immunology and Microbiology 4 6%
Engineering 3 4%
Other 6 9%
Unknown 11 16%
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 19 January 2012.
All research outputs
#18,303,566
of 22,661,413 outputs
Outputs from BMC Systems Biology
#834
of 1,142 outputs
Outputs of similar age
#196,103
of 245,768 outputs
Outputs of similar age from BMC Systems Biology
#36
of 43 outputs
Altmetric has tracked 22,661,413 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 11th percentile – i.e., 11% 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 245,768 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% 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.