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A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines

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

  • Good Attention Score compared to outputs of the same age (71st percentile)
  • Above-average Attention Score compared to outputs of the same age and source (61st percentile)

Mentioned by

patent
1 patent
reddit
1 Redditor

Citations

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5 Dimensions

Readers on

mendeley
94 Mendeley
citeulike
13 CiteULike
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Title
A lightweight, flow-based toolkit for parallel and distributed bioinformatics pipelines
Published in
BMC Bioinformatics, February 2011
DOI 10.1186/1471-2105-12-61
Pubmed ID
Authors

Marcin Cieślik, Cameron Mura

Abstract

Bioinformatic analyses typically proceed as chains of data-processing tasks. A pipeline, or 'workflow', is a well-defined protocol, with a specific structure defined by the topology of data-flow interdependencies, and a particular functionality arising from the data transformations applied at each step. In computer science, the dataflow programming (DFP) paradigm defines software systems constructed in this manner, as networks of message-passing components. Thus, bioinformatic workflows can be naturally mapped onto DFP concepts.

Mendeley readers

The data shown below were compiled from readership statistics for 94 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 9 10%
France 2 2%
Netherlands 2 2%
Japan 2 2%
Brazil 2 2%
United Kingdom 1 1%
South Africa 1 1%
Sweden 1 1%
Canada 1 1%
Other 6 6%
Unknown 67 71%

Demographic breakdown

Readers by professional status Count As %
Researcher 33 35%
Student > Ph. D. Student 16 17%
Student > Master 9 10%
Student > Bachelor 8 9%
Professor > Associate Professor 7 7%
Other 16 17%
Unknown 5 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 40 43%
Computer Science 25 27%
Biochemistry, Genetics and Molecular Biology 9 10%
Engineering 6 6%
Medicine and Dentistry 3 3%
Other 5 5%
Unknown 6 6%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 15 November 2017.
All research outputs
#3,456,212
of 12,373,386 outputs
Outputs from BMC Bioinformatics
#1,633
of 4,576 outputs
Outputs of similar age
#41,430
of 151,000 outputs
Outputs of similar age from BMC Bioinformatics
#7
of 18 outputs
Altmetric has tracked 12,373,386 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 4,576 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 63% 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 151,000 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 71% of its contemporaries.
We're also able to compare this research output to 18 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 61% of its contemporaries.