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Comparison of data-merging methods with SVM attribute selection and classification in breast cancer gene expression

Overview of attention for article published in BMC Bioinformatics, May 2012
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1 tweeter

Citations

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Readers on

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53 Mendeley
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1 CiteULike
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Title
Comparison of data-merging methods with SVM attribute selection and classification in breast cancer gene expression
Published in
BMC Bioinformatics, May 2012
DOI 10.1186/1471-2105-13-s7-s9
Pubmed ID
Authors

Vitoantonio Bevilacqua, Paolo Pannarale, Mirko Abbrescia, Claudia Cava, Angelo Paradiso, Stefania Tommasi

Abstract

DNA microarray data are used to identify genes which could be considered prognostic markers. However, due to the limited sample size of each study, the signatures are unstable in terms of the composing genes and may be limited in terms of performances. It is therefore of great interest to integrate different studies, thus increasing sample size.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 53 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 2%
Belgium 1 2%
Unknown 51 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 19 36%
Student > Master 7 13%
Student > Bachelor 7 13%
Researcher 6 11%
Professor 2 4%
Other 7 13%
Unknown 5 9%
Readers by discipline Count As %
Computer Science 20 38%
Biochemistry, Genetics and Molecular Biology 8 15%
Engineering 6 11%
Medicine and Dentistry 5 9%
Agricultural and Biological Sciences 4 8%
Other 4 8%
Unknown 6 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 09 May 2012.
All research outputs
#2,746,942
of 3,627,924 outputs
Outputs from BMC Bioinformatics
#1,872
of 2,289 outputs
Outputs of similar age
#47,762
of 73,479 outputs
Outputs of similar age from BMC Bioinformatics
#64
of 92 outputs
Altmetric has tracked 3,627,924 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,289 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 12th percentile – i.e., 12% 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 73,479 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 27th percentile – i.e., 27% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 92 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.