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pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties

Overview of attention for article published in BMC Bioinformatics, June 2005
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1 X user

Citations

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Readers on

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47 Mendeley
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2 CiteULike
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Title
pSLIP: SVM based protein subcellular localization prediction using multiple physicochemical properties
Published in
BMC Bioinformatics, June 2005
DOI 10.1186/1471-2105-6-152
Pubmed ID
Authors

Deepak Sarda, Gek Huey Chua, Kuo-Bin Li, Arun Krishnan

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

Geographical breakdown

Country Count As %
Israel 1 2%
United States 1 2%
Poland 1 2%
Australia 1 2%
Unknown 43 91%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 28%
Student > Ph. D. Student 11 23%
Student > Master 9 19%
Student > Postgraduate 3 6%
Student > Doctoral Student 3 6%
Other 4 9%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 16 34%
Computer Science 14 30%
Biochemistry, Genetics and Molecular Biology 7 15%
Engineering 3 6%
Medicine and Dentistry 1 2%
Other 0 0%
Unknown 6 13%
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 13 April 2015.
All research outputs
#17,218,945
of 25,287,709 outputs
Outputs from BMC Bioinformatics
#5,638
of 7,672 outputs
Outputs of similar age
#59,516
of 66,666 outputs
Outputs of similar age from BMC Bioinformatics
#26
of 27 outputs
Altmetric has tracked 25,287,709 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,672 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 18th percentile – i.e., 18% 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 66,666 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 5th percentile – i.e., 5% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 3rd percentile – i.e., 3% of its contemporaries scored the same or lower than it.