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Model-based Analysis of ChIP-Seq (MACS)

Overview of attention for article published in Genome Biology, September 2008
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  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
4 news outlets
blogs
2 blogs
twitter
1 X user
patent
57 patents
wikipedia
7 Wikipedia pages
q&a
1 Q&A thread

Citations

dimensions_citation
13743 Dimensions

Readers on

mendeley
6025 Mendeley
citeulike
69 CiteULike
connotea
11 Connotea
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Title
Model-based Analysis of ChIP-Seq (MACS)
Published in
Genome Biology, September 2008
DOI 10.1186/gb-2008-9-9-r137
Pubmed ID
Authors

Yong Zhang, Tao Liu, Clifford A Meyer, Jérôme Eeckhoute, David S Johnson, Bradley E Bernstein, Chad Nusbaum, Richard M Myers, Myles Brown, Wei Li, X Shirley Liu

Abstract

We present Model-based Analysis of ChIP-Seq data, MACS, which analyzes data generated by short read sequencers such as Solexa's Genome Analyzer. MACS empirically models the shift size of ChIP-Seq tags, and uses it to improve the spatial resolution of predicted binding sites. MACS also uses a dynamic Poisson distribution to effectively capture local biases in the genome, allowing for more robust predictions. MACS compares favorably to existing ChIP-Seq peak-finding algorithms, and is freely available.

X Demographics

X Demographics

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 6,025 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 106 2%
United Kingdom 36 <1%
Germany 24 <1%
France 13 <1%
Italy 11 <1%
Spain 9 <1%
China 9 <1%
Netherlands 8 <1%
Brazil 8 <1%
Other 60 <1%
Unknown 5741 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1716 28%
Researcher 1153 19%
Student > Master 592 10%
Student > Bachelor 481 8%
Student > Doctoral Student 306 5%
Other 741 12%
Unknown 1036 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 2041 34%
Biochemistry, Genetics and Molecular Biology 1837 30%
Medicine and Dentistry 246 4%
Computer Science 198 3%
Neuroscience 120 2%
Other 423 7%
Unknown 1160 19%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 65. 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 22 April 2024.
All research outputs
#671,490
of 25,837,817 outputs
Outputs from Genome Biology
#422
of 4,513 outputs
Outputs of similar age
#1,362
of 101,068 outputs
Outputs of similar age from Genome Biology
#1
of 33 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.7. This one has done particularly well, scoring higher than 90% 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 101,068 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 96% of its contemporaries.