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PyPedia: using the wiki paradigm as crowd sourcing environment for bioinformatics protocols

Overview of attention for article published in Source Code for Biology and Medicine, November 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#26 of 127)
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

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10 X users

Citations

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3 Dimensions

Readers on

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29 Mendeley
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Title
PyPedia: using the wiki paradigm as crowd sourcing environment for bioinformatics protocols
Published in
Source Code for Biology and Medicine, November 2015
DOI 10.1186/s13029-015-0042-6
Pubmed ID
Authors

Alexandros Kanterakis, Joël Kuiper, George Potamias, Morris A. Swertz

Abstract

Today researchers can choose from many bioinformatics protocols for all types of life sciences research, computational environments and coding languages. Although the majority of these are open source, few of them possess all virtues to maximize reuse and promote reproducible science. Wikipedia has proven a great tool to disseminate information and enhance collaboration between users with varying expertise and background to author qualitative content via crowdsourcing. However, it remains an open question whether the wiki paradigm can be applied to bioinformatics protocols. We piloted PyPedia, a wiki where each article is both implementation and documentation of a bioinformatics computational protocol in the python language. Hyperlinks within the wiki can be used to compose complex workflows and induce reuse. A RESTful API enables code execution outside the wiki. Initial content of PyPedia contains articles for population statistics, bioinformatics format conversions and genotype imputation. Use of the easy to learn wiki syntax effectively lowers the barriers to bring expert programmers and less computer savvy researchers on the same page. PyPedia demonstrates how wiki can provide a collaborative development, sharing and even execution environment for biologists and bioinformaticians that complement existing resources, useful for local and multi-center research teams. PyPedia is available online at: http://www.pypedia.com. The source code and installation instructions are available at: https://github.com/kantale/PyPedia_server. The PyPedia python library is available at: https://github.com/kantale/pypedia. PyPedia is open-source, available under the BSD 2-Clause License.

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 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 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 3%
Chile 1 3%
Ghana 1 3%
Unknown 26 90%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 21%
Researcher 5 17%
Student > Master 4 14%
Librarian 2 7%
Professor > Associate Professor 2 7%
Other 5 17%
Unknown 5 17%
Readers by discipline Count As %
Computer Science 9 31%
Biochemistry, Genetics and Molecular Biology 3 10%
Agricultural and Biological Sciences 3 10%
Medicine and Dentistry 2 7%
Social Sciences 2 7%
Other 6 21%
Unknown 4 14%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 February 2016.
All research outputs
#4,315,953
of 23,577,761 outputs
Outputs from Source Code for Biology and Medicine
#26
of 127 outputs
Outputs of similar age
#69,778
of 390,067 outputs
Outputs of similar age from Source Code for Biology and Medicine
#2
of 6 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done well and is in the 81st percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 127 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done well, scoring higher than 79% 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 390,067 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 82% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 4 of them.