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Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer

Overview of attention for article published in BMC Systems Biology, December 2012
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  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
2 tweeters

Citations

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28 Dimensions

Readers on

mendeley
58 Mendeley
citeulike
1 CiteULike
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Title
Integrative pathway analysis of genome-wide association studies and gene expression data in prostate cancer
Published in
BMC Systems Biology, December 2012
DOI 10.1186/1752-0509-6-s3-s13
Pubmed ID
Authors

Peilin Jia, Yang Liu, Zhongming Zhao

Abstract

Pathway analysis of large-scale omics data assists us with the examination of the cumulative effects of multiple functionally related genes, which are difficult to detect using the traditional single gene/marker analysis. So far, most of the genomic studies have been conducted in a single domain, e.g., by genome-wide association studies (GWAS) or microarray gene expression investigation. A combined analysis of disease susceptibility genes across multiple platforms at the pathway level is an urgent need because it can reveal more reliable and more biologically important information.

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

Geographical breakdown

Country Count As %
Lithuania 1 2%
Israel 1 2%
United Kingdom 1 2%
Argentina 1 2%
United States 1 2%
Unknown 53 91%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 26%
Researcher 13 22%
Professor > Associate Professor 6 10%
Student > Bachelor 5 9%
Student > Master 4 7%
Other 10 17%
Unknown 5 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 53%
Biochemistry, Genetics and Molecular Biology 9 16%
Computer Science 4 7%
Mathematics 2 3%
Engineering 2 3%
Other 4 7%
Unknown 6 10%

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 05 March 2013.
All research outputs
#12,311,860
of 18,796,975 outputs
Outputs from BMC Systems Biology
#636
of 1,127 outputs
Outputs of similar age
#97,522
of 163,791 outputs
Outputs of similar age from BMC Systems Biology
#8
of 17 outputs
Altmetric has tracked 18,796,975 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,127 research outputs from this source. They receive a mean Attention Score of 3.5. 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 163,791 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.