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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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1 tweeter

Citations

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68 Dimensions

Readers on

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157 Mendeley
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2 CiteULike
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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.

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

Geographical breakdown

Country Count As %
United States 2 1%
France 2 1%
Spain 2 1%
Estonia 2 1%
Italy 1 <1%
South Africa 1 <1%
Ireland 1 <1%
Switzerland 1 <1%
Unknown 145 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 44 28%
Student > Ph. D. Student 40 25%
Student > Master 16 10%
Professor > Associate Professor 9 6%
Student > Postgraduate 7 4%
Other 21 13%
Unknown 20 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 27%
Biochemistry, Genetics and Molecular Biology 27 17%
Medicine and Dentistry 17 11%
Immunology and Microbiology 6 4%
Mathematics 6 4%
Other 29 18%
Unknown 30 19%

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
#11,549,661
of 14,573,111 outputs
Outputs from BMC Bioinformatics
#4,483
of 5,420 outputs
Outputs of similar age
#177,754
of 251,332 outputs
Outputs of similar age from BMC Bioinformatics
#312
of 368 outputs
Altmetric has tracked 14,573,111 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,420 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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We're also able to compare this research output to 368 others from the same source and published within six weeks on either side of this one. This one is in the 4th percentile – i.e., 4% of its contemporaries scored the same or lower than it.