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IPRStats: visualization of the functional potential of an InterProScan run

Overview of attention for article published in BMC Bioinformatics, December 2010
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Mentioned by

twitter
3 tweeters

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
42 Mendeley
citeulike
4 CiteULike
connotea
1 Connotea
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Title
IPRStats: visualization of the functional potential of an InterProScan run
Published in
BMC Bioinformatics, December 2010
DOI 10.1186/1471-2105-11-s12-s13
Pubmed ID
Authors

Ryan J Kelly, David E Vincent, Iddo Friedberg

Abstract

InterPro is a collection of protein signatures for the classification and automated annotation of proteins. Interproscan is a software tool that scans protein sequences against Interpro member databases using a variety of profile-based, hidden markov model and positional specific score matrix methods. It not only combines a set of analysis tools, but also performs data look-up from various sources, as well as some redundancy removal. Interproscan is robust and scalable, able to perform on any machine from a netbook to a large cluster. However, when performing whole-genome or metagenome analysis, there is a need for a fast statistical visualization of the results to have good initial grasp on the functional potential of the sequences in the analyzed data set. This is especially important when analyzing and comparing metagenomic or metaproteomic data-sets.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters 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 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
France 2 5%
United States 1 2%
Sweden 1 2%
Italy 1 2%
Unknown 37 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 40%
Student > Ph. D. Student 7 17%
Student > Master 7 17%
Student > Doctoral Student 4 10%
Student > Bachelor 2 5%
Other 4 10%
Unknown 1 2%
Readers by discipline Count As %
Agricultural and Biological Sciences 23 55%
Biochemistry, Genetics and Molecular Biology 12 29%
Computer Science 3 7%
Mathematics 1 2%
Social Sciences 1 2%
Other 1 2%
Unknown 1 2%

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 06 March 2013.
All research outputs
#12,880,627
of 21,344,814 outputs
Outputs from BMC Bioinformatics
#4,241
of 6,922 outputs
Outputs of similar age
#92,395
of 170,608 outputs
Outputs of similar age from BMC Bioinformatics
#22
of 37 outputs
Altmetric has tracked 21,344,814 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 6,922 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 38th percentile – i.e., 38% 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 170,608 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 37 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.