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Active enhancer positions can be accurately predicted from chromatin marks and collective sequence motif data

Overview of attention for article published in BMC Systems Biology, December 2013
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Title
Active enhancer positions can be accurately predicted from chromatin marks and collective sequence motif data
Published in
BMC Systems Biology, December 2013
DOI 10.1186/1752-0509-7-s6-s16
Pubmed ID
Authors

Agnieszka Podsiadło, Mariusz Wrzesień, Wiesław Paja, Witold Rudnicki, Bartek Wilczyński

Abstract

Transcriptional regulation in multi-cellular organisms is a complex process involving multiple modular regulatory elements for each gene. Building whole-genome models of transcriptional networks requires mapping all relevant enhancers and then linking them to target genes. Previous methods of enhancer identification based either on sequence information or on epigenetic marks have different limitations stemming from incompleteness of each of these datasets taken separately.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 32 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Finland 1 3%
Hong Kong 1 3%
Poland 1 3%
Unknown 28 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 44%
Student > Ph. D. Student 11 34%
Student > Bachelor 1 3%
Student > Master 1 3%
Professor 1 3%
Other 1 3%
Unknown 3 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 13 41%
Computer Science 6 19%
Biochemistry, Genetics and Molecular Biology 4 13%
Physics and Astronomy 2 6%
Medicine and Dentistry 1 3%
Other 0 0%
Unknown 6 19%

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 07 November 2014.
All research outputs
#16,628,262
of 18,796,975 outputs
Outputs from BMC Systems Biology
#986
of 1,127 outputs
Outputs of similar age
#202,295
of 243,754 outputs
Outputs of similar age from BMC Systems Biology
#56
of 67 outputs
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So far Altmetric has tracked 1,127 research outputs from this source. They receive a mean Attention Score of 3.5. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 67 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.