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Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information

Overview of attention for article published in BMC Medical Genomics, January 2010
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Mentioned by

twitter
2 tweeters

Citations

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85 Dimensions

Readers on

mendeley
115 Mendeley
citeulike
7 CiteULike
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Title
Systematic analysis, comparison, and integration of disease based human genetic association data and mouse genetic phenotypic information
Published in
BMC Medical Genomics, January 2010
DOI 10.1186/1755-8794-3-1
Pubmed ID
Authors

Yonqing Zhang, Supriyo De, John R Garner, Kirstin Smith, S Alex Wang, Kevin G Becker

Abstract

The genetic contributions to human common disorders and mouse genetic models of disease are complex and often overlapping. In common human diseases, unlike classical Mendelian disorders, genetic factors generally have small effect sizes, are multifactorial, and are highly pleiotropic. Likewise, mouse genetic models of disease often have pleiotropic and overlapping phenotypes. Moreover, phenotypic descriptions in the literature in both human and mouse are often poorly characterized and difficult to compare directly.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 115 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 7 6%
Germany 5 4%
United Kingdom 3 3%
Spain 2 2%
Portugal 1 <1%
Iceland 1 <1%
Korea, Republic of 1 <1%
Netherlands 1 <1%
Canada 1 <1%
Other 1 <1%
Unknown 92 80%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 31%
Student > Ph. D. Student 31 27%
Student > Master 11 10%
Student > Bachelor 7 6%
Professor > Associate Professor 6 5%
Other 24 21%
Readers by discipline Count As %
Agricultural and Biological Sciences 66 57%
Biochemistry, Genetics and Molecular Biology 14 12%
Medicine and Dentistry 13 11%
Computer Science 8 7%
Unspecified 6 5%
Other 8 7%

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 25 May 2012.
All research outputs
#7,490,590
of 12,986,898 outputs
Outputs from BMC Medical Genomics
#332
of 630 outputs
Outputs of similar age
#58,317
of 118,703 outputs
Outputs of similar age from BMC Medical Genomics
#4
of 4 outputs
Altmetric has tracked 12,986,898 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 630 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 43rd percentile – i.e., 43% 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 118,703 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one.