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DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins

Overview of attention for article published in BMC Bioinformatics, March 2017
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Mentioned by

twitter
1 tweeter

Citations

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11 Dimensions

Readers on

mendeley
30 Mendeley
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Title
DIRProt: a computational approach for discriminating insecticide resistant proteins from non-resistant proteins
Published in
BMC Bioinformatics, March 2017
DOI 10.1186/s12859-017-1587-y
Pubmed ID
Authors

Prabina Kumar Meher, Tanmaya Kumar Sahu, Anjali Banchariya, Atmakuri Ramakrishna Rao

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

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 27%
Student > Master 5 17%
Researcher 2 7%
Student > Bachelor 2 7%
Unspecified 1 3%
Other 2 7%
Unknown 10 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 23%
Agricultural and Biological Sciences 4 13%
Computer Science 3 10%
Environmental Science 1 3%
Business, Management and Accounting 1 3%
Other 3 10%
Unknown 11 37%

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 02 November 2018.
All research outputs
#8,612,292
of 13,726,653 outputs
Outputs from BMC Bioinformatics
#3,505
of 5,107 outputs
Outputs of similar age
#188,954
of 308,034 outputs
Outputs of similar age from BMC Bioinformatics
#268
of 413 outputs
Altmetric has tracked 13,726,653 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,107 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 22nd percentile – i.e., 22% 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 308,034 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 413 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.