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PheMaDB: A solution for storage, retrieval, and analysis of high throughput phenotype data

Overview of attention for article published in BMC Bioinformatics, April 2011
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About this Attention Score

  • Average Attention Score compared to outputs of the same age and source

Mentioned by

wikipedia
2 Wikipedia pages

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
46 Mendeley
citeulike
4 CiteULike
connotea
1 Connotea
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Title
PheMaDB: A solution for storage, retrieval, and analysis of high throughput phenotype data
Published in
BMC Bioinformatics, April 2011
DOI 10.1186/1471-2105-12-109
Pubmed ID
Authors

Wenling E Chang, Keri Sarver, Brandon W Higgs, Timothy D Read, Nichole ME Nolan, Carol E Chapman, Kimberly A Bishop-Lilly, Shanmuga Sozhamannan

Mendeley readers

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 States 1 2%
Sweden 1 2%
Unknown 44 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 30%
Researcher 13 28%
Student > Master 4 9%
Student > Postgraduate 3 7%
Student > Bachelor 2 4%
Other 6 13%
Unknown 4 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 28 61%
Biochemistry, Genetics and Molecular Biology 5 11%
Engineering 4 9%
Business, Management and Accounting 1 2%
Unspecified 1 2%
Other 2 4%
Unknown 5 11%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 11 November 2013.
All research outputs
#7,647,833
of 23,285,523 outputs
Outputs from BMC Bioinformatics
#3,071
of 7,374 outputs
Outputs of similar age
#40,639
of 110,595 outputs
Outputs of similar age from BMC Bioinformatics
#30
of 66 outputs
Altmetric has tracked 23,285,523 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,374 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 50% of its peers.
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 110,595 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 66 others from the same source and published within six weeks on either side of this one. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.