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A novel approach for biomarker selection and the integration of repeated measures experiments from two assays

Overview of attention for article published in BMC Bioinformatics, December 2012
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Title
A novel approach for biomarker selection and the integration of repeated measures experiments from two assays
Published in
BMC Bioinformatics, December 2012
DOI 10.1186/1471-2105-13-325
Pubmed ID
Authors

Benoit Liquet, Kim-Anh Lê Cao, Hakim Hocini, Rodolphe Thiébaut

Abstract

High throughput 'omics' experiments are usually designed to compare changes observed between different conditions (or interventions) and to identify biomarkers capable of characterizing each condition. We consider the complex structure of repeated measurements from different assays where different conditions are applied on the same subjects.

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

Geographical breakdown

Country Count As %
France 2 1%
Estonia 2 1%
United States 2 1%
Spain 2 1%
South Africa 1 <1%
Switzerland 1 <1%
Ireland 1 <1%
Italy 1 <1%
Unknown 179 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 49 26%
Student > Ph. D. Student 45 24%
Student > Master 17 9%
Professor > Associate Professor 11 6%
Other 9 5%
Other 29 15%
Unknown 31 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 45 24%
Biochemistry, Genetics and Molecular Biology 35 18%
Medicine and Dentistry 17 9%
Mathematics 7 4%
Computer Science 6 3%
Other 34 18%
Unknown 47 25%
Attention Score in Context

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 06 December 2012.
All research outputs
#20,176,348
of 22,689,790 outputs
Outputs from BMC Bioinformatics
#6,825
of 7,252 outputs
Outputs of similar age
#246,509
of 278,002 outputs
Outputs of similar age from BMC Bioinformatics
#121
of 127 outputs
Altmetric has tracked 22,689,790 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,252 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 127 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.