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EpiMINE, a computational program for mining epigenomic data

Overview of attention for article published in Epigenetics & Chromatin, September 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

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22 X users

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27 Mendeley
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Title
EpiMINE, a computational program for mining epigenomic data
Published in
Epigenetics & Chromatin, September 2016
DOI 10.1186/s13072-016-0095-z
Pubmed ID
Authors

SriGanesh Jammula, Diego Pasini

Abstract

In epigenetic research, both the increasing ease of high-throughput sequencing and a greater interest in genome-wide studies have resulted in an exponential flooding of epigenetic-related data in public domain. This creates an opportunity for exploring data outside the limits of any specific query-centred study. Such data have to undergo standard primary analyses that are accessible with multiple well-stabilized programs. Further downstream analyses, such as genome-wide comparative, correlative and quantitative analyses, are critical in deciphering key biological features. However, these analyses are only accessible for computational researchers and completely lack platforms capable of handling, analysing and linking multiple interdisciplinary datasets with efficient analytical methods. Here, we present EpiMINE, a program for mining epigenomic data. It is a user-friendly, stand-alone computational program designed to support multiple datasets, for performing genome-wide correlative and quantitative analysis of ChIP-seq and RNA-seq data. Using data available from the ENCODE project, we illustrated several features of EpiMINE through different biological scenarios to show how easy some known observations can be verified. These results highlight how these approaches can be helpful in identifying novel biological features. EpiMINE performs different kinds of genome-wide quantitative and correlative analyses, using ChIP-seq- and RNA-seq-related datasets. Its framework enables it to be used by both experimental and computational researchers. EpiMINE can be downloaded from https://sourceforge.net/projects/epimine/.

X Demographics

X Demographics

The data shown below were collected from the profiles of 22 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Sweden 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 26%
Student > Ph. D. Student 6 22%
Professor 2 7%
Student > Postgraduate 2 7%
Student > Master 1 4%
Other 2 7%
Unknown 7 26%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 37%
Agricultural and Biological Sciences 4 15%
Medicine and Dentistry 2 7%
Computer Science 1 4%
Economics, Econometrics and Finance 1 4%
Other 1 4%
Unknown 8 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 18 June 2017.
All research outputs
#2,615,400
of 22,890,496 outputs
Outputs from Epigenetics & Chromatin
#86
of 567 outputs
Outputs of similar age
#46,514
of 322,600 outputs
Outputs of similar age from Epigenetics & Chromatin
#2
of 19 outputs
Altmetric has tracked 22,890,496 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 567 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has done well, scoring higher than 84% 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 322,600 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.