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GeSICA: Genome segmentation from intra-chromosomal associations

Overview of attention for article published in BMC Genomics, May 2012
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Title
GeSICA: Genome segmentation from intra-chromosomal associations
Published in
BMC Genomics, May 2012
DOI 10.1186/1471-2164-13-164
Pubmed ID
Authors

Lin Liu, Yiqian Zhang, Jianxing Feng, Ning Zheng, Junfeng Yin, Yong Zhang

Abstract

Various aspects of genome organization have been explored based on data from distinct technologies, including histone modification ChIP-Seq, 3C, and its derivatives. Recently developed Hi-C techniques enable the genome wide mapping of DNA interactomes, thereby providing the opportunity to study genome organization in detail, but these methods also pose challenges in methodology development.

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

Geographical breakdown

Country Count As %
United States 4 9%
Portugal 1 2%
Germany 1 2%
United Kingdom 1 2%
Lithuania 1 2%
Russia 1 2%
Denmark 1 2%
Unknown 36 78%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 30%
Student > Ph. D. Student 13 28%
Professor 4 9%
Student > Bachelor 3 7%
Professor > Associate Professor 3 7%
Other 6 13%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 27 59%
Biochemistry, Genetics and Molecular Biology 6 13%
Computer Science 2 4%
Engineering 2 4%
Environmental Science 1 2%
Other 4 9%
Unknown 4 9%
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 10 May 2012.
All research outputs
#18,305,773
of 22,665,794 outputs
Outputs from BMC Genomics
#8,144
of 10,615 outputs
Outputs of similar age
#126,211
of 163,497 outputs
Outputs of similar age from BMC Genomics
#60
of 80 outputs
Altmetric has tracked 22,665,794 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 10,615 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 163,497 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 80 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.