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Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline

Overview of attention for article published in BMC Bioinformatics, December 2013
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

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1 X user
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1 patent

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174 Mendeley
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3 CiteULike
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Title
Meta-analysis methods for combining multiple expression profiles: comparisons, statistical characterization and an application guideline
Published in
BMC Bioinformatics, December 2013
DOI 10.1186/1471-2105-14-368
Pubmed ID
Authors

Lun-Ching Chang, Hui-Min Lin, Etienne Sibille, George C Tseng

Abstract

As high-throughput genomic technologies become accurate and affordable, an increasing number of data sets have been accumulated in the public domain and genomic information integration and meta-analysis have become routine in biomedical research. In this paper, we focus on microarray meta-analysis, where multiple microarray studies with relevant biological hypotheses are combined in order to improve candidate marker detection. Many methods have been developed and applied in the literature, but their performance and properties have only been minimally investigated. There is currently no clear conclusion or guideline as to the proper choice of a meta-analysis method given an application; the decision essentially requires both statistical and biological considerations.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 174 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 3 2%
Germany 2 1%
Netherlands 1 <1%
Brazil 1 <1%
New Caledonia 1 <1%
Sweden 1 <1%
United States 1 <1%
Unknown 164 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 48 28%
Researcher 36 21%
Student > Master 15 9%
Student > Bachelor 14 8%
Other 11 6%
Other 27 16%
Unknown 23 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 47 27%
Biochemistry, Genetics and Molecular Biology 31 18%
Medicine and Dentistry 24 14%
Computer Science 19 11%
Mathematics 8 5%
Other 14 8%
Unknown 31 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 May 2018.
All research outputs
#7,193,307
of 22,738,543 outputs
Outputs from BMC Bioinformatics
#2,858
of 7,266 outputs
Outputs of similar age
#88,117
of 306,115 outputs
Outputs of similar age from BMC Bioinformatics
#42
of 110 outputs
Altmetric has tracked 22,738,543 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 7,266 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 59% 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 306,115 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 70% of its contemporaries.
We're also able to compare this research output to 110 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 59% of its contemporaries.