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Biopython: freely available Python tools for computational molecular biology and bioinformatics

Overview of attention for article published in Bioinformatics, March 2009
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
1 news outlet
blogs
3 blogs
policy
1 policy source
twitter
8 X users
patent
7 patents
wikipedia
11 Wikipedia pages

Citations

dimensions_citation
4060 Dimensions

Readers on

mendeley
3077 Mendeley
citeulike
89 CiteULike
connotea
5 Connotea
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Title
Biopython: freely available Python tools for computational molecular biology and bioinformatics
Published in
Bioinformatics, March 2009
DOI 10.1093/bioinformatics/btp163
Pubmed ID
Authors

Peter J. A. Cock, Tiago Antao, Jeffrey T. Chang, Brad A. Chapman, Cymon J. Cox, Andrew Dalke, Iddo Friedberg, Thomas Hamelryck, Frank Kauff, Bartek Wilczynski, Michiel J. L. de Hoon

Abstract

The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 3,077 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 50 2%
United Kingdom 23 <1%
Germany 18 <1%
Brazil 12 <1%
France 10 <1%
Italy 8 <1%
Spain 8 <1%
Belgium 7 <1%
Netherlands 7 <1%
Other 68 2%
Unknown 2866 93%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 668 22%
Researcher 480 16%
Student > Master 428 14%
Student > Bachelor 425 14%
Student > Doctoral Student 133 4%
Other 365 12%
Unknown 578 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 909 30%
Biochemistry, Genetics and Molecular Biology 740 24%
Computer Science 228 7%
Chemistry 102 3%
Engineering 87 3%
Other 353 11%
Unknown 658 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 22 April 2024.
All research outputs
#979,923
of 25,954,278 outputs
Outputs from Bioinformatics
#254
of 12,950 outputs
Outputs of similar age
#2,366
of 109,756 outputs
Outputs of similar age from Bioinformatics
#2
of 73 outputs
Altmetric has tracked 25,954,278 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 12,950 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.1. This one has done particularly well, scoring higher than 98% 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 109,756 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 97% of its contemporaries.
We're also able to compare this research output to 73 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.