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Analysis method of epigenetic DNA methylation to dynamically investigate the functional activity of transcription factors in gene expression

Overview of attention for article published in BMC Genomics, October 2012
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Title
Analysis method of epigenetic DNA methylation to dynamically investigate the functional activity of transcription factors in gene expression
Published in
BMC Genomics, October 2012
DOI 10.1186/1471-2164-13-532
Pubmed ID
Authors

Weixing Feng, Zengchao Dong, Bo He, Kejun Wang

Abstract

DNA methylation is a fundamental component of epigenetic modification, which is intimately involved in the regulation of gene expression. One important DNA methylation pathway reduces the abilities of transcription factors to bind to gene promoter regions. Although many experiments have been designed to measure genome-wide DNA methylation levels at high resolution, the meaning of these different DNA methylation levels on transcription factor binding abilities remains poorly understood. We have, therefore, developed a method to quantitatively explore the extent to which DNA methylation levels can significantly reduce or even abolish the binding of certain transcription factors, resulting in reduced or non-expression of flanking genes. This method allows transcription factors that are functionally active in gene expression to be investigated.

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The data shown below were collected from the profiles of 2 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 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 2%
Unknown 46 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 28%
Student > Ph. D. Student 7 15%
Student > Doctoral Student 6 13%
Student > Master 6 13%
Student > Bachelor 4 9%
Other 6 13%
Unknown 5 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 20 43%
Biochemistry, Genetics and Molecular Biology 11 23%
Computer Science 3 6%
Environmental Science 1 2%
Nursing and Health Professions 1 2%
Other 4 9%
Unknown 7 15%
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 08 November 2012.
All research outputs
#16,048,318
of 25,374,917 outputs
Outputs from BMC Genomics
#6,103
of 11,244 outputs
Outputs of similar age
#116,853
of 191,704 outputs
Outputs of similar age from BMC Genomics
#101
of 180 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% 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 41st percentile – i.e., 41% 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 191,704 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 36th percentile – i.e., 36% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 180 others from the same source and published within six weeks on either side of this one. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.