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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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  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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2 X users

Citations

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28 Dimensions

Readers on

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61 Mendeley
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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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 61 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 56 92%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 26%
Researcher 13 21%
Student > Bachelor 6 10%
Professor > Associate Professor 6 10%
Student > Master 5 8%
Other 10 16%
Unknown 5 8%
Readers by discipline Count As %
Agricultural and Biological Sciences 31 51%
Biochemistry, Genetics and Molecular Biology 10 16%
Computer Science 4 7%
Mathematics 2 3%
Medicine and Dentistry 2 3%
Other 6 10%
Unknown 6 10%
Attention Score in Context

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
#14,619,971
of 22,699,621 outputs
Outputs from BMC Systems Biology
#595
of 1,142 outputs
Outputs of similar age
#161,691
of 261,321 outputs
Outputs of similar age from BMC Systems Biology
#25
of 56 outputs
Altmetric has tracked 22,699,621 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,142 research outputs from this source. They receive a mean Attention Score of 3.6. This one is in the 47th percentile – i.e., 47% 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 261,321 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 56 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 55% of its contemporaries.