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PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources

Overview of attention for article published in BMC Bioinformatics, March 2019
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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 (88th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

Mentioned by

twitter
33 X users

Readers on

mendeley
31 Mendeley
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Title
PyCellBase, an efficient python package for easy retrieval of biological data from heterogeneous sources
Published in
BMC Bioinformatics, March 2019
DOI 10.1186/s12859-019-2726-4
Pubmed ID
Authors

Daniel Perez-Gil, Francisco J. Lopez, Joaquin Dopazo, Pablo Marin-Garcia, Augusto Rendon, Ignacio Medina

X Demographics

X Demographics

The data shown below were collected from the profiles of 33 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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 16%
Researcher 5 16%
Student > Master 5 16%
Student > Ph. D. Student 4 13%
Student > Postgraduate 3 10%
Other 4 13%
Unknown 5 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 35%
Agricultural and Biological Sciences 5 16%
Business, Management and Accounting 2 6%
Computer Science 2 6%
Chemical Engineering 1 3%
Other 3 10%
Unknown 7 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 12 April 2019.
All research outputs
#1,857,350
of 25,247,084 outputs
Outputs from BMC Bioinformatics
#363
of 7,664 outputs
Outputs of similar age
#41,077
of 358,384 outputs
Outputs of similar age from BMC Bioinformatics
#11
of 162 outputs
Altmetric has tracked 25,247,084 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,664 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 95% 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 358,384 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 88% of its contemporaries.
We're also able to compare this research output to 162 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 93% of its contemporaries.