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eXframe: reusable framework for storage, analysis and visualization of genomics experiments

Overview of attention for article published in BMC Bioinformatics, November 2011
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (77th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (60th percentile)

Mentioned by

twitter
3 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
5 Dimensions

Readers on

mendeley
67 Mendeley
citeulike
6 CiteULike
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Title
eXframe: reusable framework for storage, analysis and visualization of genomics experiments
Published in
BMC Bioinformatics, November 2011
DOI 10.1186/1471-2105-12-452
Pubmed ID
Authors

Amit U Sinha, Emily Merrill, Scott A Armstrong, Tim W Clark, Sudeshna Das

Abstract

Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 5 7%
United Kingdom 2 3%
Netherlands 2 3%
Bangladesh 1 1%
Brazil 1 1%
Sweden 1 1%
Germany 1 1%
Switzerland 1 1%
India 1 1%
Other 2 3%
Unknown 50 75%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 30%
Student > Ph. D. Student 9 13%
Student > Bachelor 7 10%
Professor > Associate Professor 6 9%
Student > Master 6 9%
Other 12 18%
Unknown 7 10%
Readers by discipline Count As %
Agricultural and Biological Sciences 22 33%
Computer Science 11 16%
Medicine and Dentistry 9 13%
Biochemistry, Genetics and Molecular Biology 5 7%
Nursing and Health Professions 3 4%
Other 10 15%
Unknown 7 10%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 23 October 2017.
All research outputs
#5,845,290
of 22,659,164 outputs
Outputs from BMC Bioinformatics
#2,168
of 7,236 outputs
Outputs of similar age
#51,347
of 239,286 outputs
Outputs of similar age from BMC Bioinformatics
#43
of 110 outputs
Altmetric has tracked 22,659,164 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 7,236 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one has gotten more attention than average, scoring higher than 69% 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 239,286 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 77% of its contemporaries.
We're also able to compare this research output to 110 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 60% of its contemporaries.