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openBIS: a flexible framework for managing and analyzing complex data in biology research

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

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (96th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

blogs
3 blogs
twitter
8 tweeters
googleplus
2 Google+ users

Citations

dimensions_citation
71 Dimensions

Readers on

mendeley
207 Mendeley
citeulike
10 CiteULike
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Title
openBIS: a flexible framework for managing and analyzing complex data in biology research
Published in
BMC Bioinformatics, January 2011
DOI 10.1186/1471-2105-12-468
Pubmed ID
Authors

Angela Bauch, Izabela Adamczyk, Piotr Buczek, Franz-Josef Elmer, Kaloyan Enimanev, Pawel Glyzewski, Manuel Kohler, Tomasz Pylak, Andreas Quandt, Chandrasekhar Ramakrishnan, Christian Beisel, Lars Malmstrom, Ruedi Aebersold, Bernd Rinn

Abstract

Modern data generation techniques used in distributed systems biology research projects often create datasets of enormous size and diversity. We argue that in order to overcome the challenge of managing those large quantitative datasets and maximise the biological information extracted from them, a sound information system is required. Ease of integration with data analysis pipelines and other computational tools is a key requirement for it.

Twitter Demographics

The data shown below were collected from the profiles of 8 tweeters 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 207 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 3%
Germany 4 2%
Netherlands 4 2%
Switzerland 3 1%
United Kingdom 2 <1%
Brazil 2 <1%
Luxembourg 2 <1%
Australia 1 <1%
Italy 1 <1%
Other 8 4%
Unknown 174 84%

Demographic breakdown

Readers by professional status Count As %
Researcher 77 37%
Student > Ph. D. Student 48 23%
Student > Master 22 11%
Other 10 5%
Professor > Associate Professor 10 5%
Other 32 15%
Unknown 8 4%
Readers by discipline Count As %
Agricultural and Biological Sciences 79 38%
Computer Science 40 19%
Biochemistry, Genetics and Molecular Biology 24 12%
Medicine and Dentistry 8 4%
Environmental Science 6 3%
Other 34 16%
Unknown 16 8%

Attention Score in Context

This research output has an Altmetric Attention Score of 26. 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 28 October 2020.
All research outputs
#848,616
of 16,293,064 outputs
Outputs from BMC Bioinformatics
#126
of 5,890 outputs
Outputs of similar age
#8,023
of 218,791 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 346 outputs
Altmetric has tracked 16,293,064 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 5,890 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 97% 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 218,791 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 96% of its contemporaries.
We're also able to compare this research output to 346 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 97% of its contemporaries.