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An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

Overview of attention for article published in BMC Genomics, January 2012
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Title
An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies
Published in
BMC Genomics, January 2012
DOI 10.1186/1471-2164-13-42
Pubmed ID
Authors

Michiel E Adriaens, Magali Jaillard, Lars MT Eijssen, Claus-Dieter Mayer, Chris TA Evelo

Abstract

The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users 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 34 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 6%
Netherlands 1 3%
United Kingdom 1 3%
Unknown 30 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 32%
Student > Master 5 15%
Student > Doctoral Student 4 12%
Student > Ph. D. Student 4 12%
Professor > Associate Professor 3 9%
Other 6 18%
Unknown 1 3%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 50%
Engineering 3 9%
Computer Science 3 9%
Medicine and Dentistry 2 6%
Biochemistry, Genetics and Molecular Biology 2 6%
Other 4 12%
Unknown 3 9%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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
#15,740,207
of 25,374,917 outputs
Outputs from BMC Genomics
#5,756
of 11,244 outputs
Outputs of similar age
#160,889
of 252,191 outputs
Outputs of similar age from BMC Genomics
#60
of 118 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 46th percentile – i.e., 46% 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 252,191 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 118 others from the same source and published within six weeks on either side of this one. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.