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HAT: Hypergeometric Analysis of Tiling-arrays with application to promoter-GeneChip data

Overview of attention for article published in BMC Bioinformatics, May 2010
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Mentioned by

wikipedia
1 Wikipedia page

Citations

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8 Dimensions

Readers on

mendeley
29 Mendeley
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4 CiteULike
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Title
HAT: Hypergeometric Analysis of Tiling-arrays with application to promoter-GeneChip data
Published in
BMC Bioinformatics, May 2010
DOI 10.1186/1471-2105-11-275
Pubmed ID
Authors

Erdogan Taskesen, Renee Beekman, Jeroen de Ridder, Bas J Wouters, Justine K Peeters, Ivo P Touw, Marcel JT Reinders, Ruud Delwel

Abstract

Tiling-arrays are applicable to multiple types of biological research questions. Due to its advantages (high sensitivity, resolution, unbiased), the technology is often employed in genome-wide investigations. A major challenge in the analysis of tiling-array data is to define regions-of-interest, i.e., contiguous probes with increased signal intensity (as a result of hybridization of labeled DNA) in a region. Currently, no standard criteria are available to define these regions-of-interest as there is no single probe intensity cut-off level, different regions-of-interest can contain various numbers of probes, and can vary in genomic width. Furthermore, the chromosomal distance between neighboring probes can vary across the genome among different arrays.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Mexico 1 3%
Denmark 1 3%
United States 1 3%
Luxembourg 1 3%
Unknown 24 83%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 28%
Student > Ph. D. Student 8 28%
Professor > Associate Professor 3 10%
Other 2 7%
Lecturer 2 7%
Other 3 10%
Unknown 3 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 14 48%
Medicine and Dentistry 4 14%
Computer Science 3 10%
Biochemistry, Genetics and Molecular Biology 2 7%
Mathematics 1 3%
Other 2 7%
Unknown 3 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 June 2012.
All research outputs
#7,454,298
of 22,789,076 outputs
Outputs from BMC Bioinformatics
#3,023
of 7,279 outputs
Outputs of similar age
#33,481
of 94,324 outputs
Outputs of similar age from BMC Bioinformatics
#36
of 74 outputs
Altmetric has tracked 22,789,076 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,279 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 50% 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 94,324 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.