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Pattern search in BioPAX models

Overview of attention for article published in Bioinformatics, September 2013
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  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
3 tweeters

Citations

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22 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
2 CiteULike
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Title
Pattern search in BioPAX models
Published in
Bioinformatics, September 2013
DOI 10.1093/bioinformatics/btt539
Pubmed ID
Authors

Özgün Babur, Bülent Arman Aksoy, Igor Rodchenkov, Selçuk Onur Sümer, Chris Sander, Emek Demir

Abstract

BioPAX is a standard language for representing complex cellular processes, including metabolic networks, signal transduction and gene regulation. Owing to the inherent complexity of a BioPAX model, searching for a specific type of subnetwork can be non-trivial and difficult.

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

Geographical breakdown

Country Count As %
United Kingdom 3 7%
Ukraine 1 2%
Hungary 1 2%
Spain 1 2%
United States 1 2%
Unknown 39 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 17 37%
Student > Ph. D. Student 10 22%
Student > Bachelor 5 11%
Student > Postgraduate 4 9%
Other 3 7%
Other 7 15%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 17 37%
Agricultural and Biological Sciences 14 30%
Computer Science 11 24%
Medicine and Dentistry 3 7%
Mathematics 1 2%
Other 0 0%

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 23 December 2013.
All research outputs
#10,425,775
of 17,435,797 outputs
Outputs from Bioinformatics
#8,121
of 10,651 outputs
Outputs of similar age
#89,588
of 175,025 outputs
Outputs of similar age from Bioinformatics
#99
of 149 outputs
Altmetric has tracked 17,435,797 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 10,651 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 20th percentile – i.e., 20% 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 175,025 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 149 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.