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Molmil: a molecular viewer for the PDB and beyond

Overview of attention for article published in Journal of Cheminformatics, August 2016
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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 (85th percentile)
  • Good Attention Score compared to outputs of the same age and source (71st percentile)

Mentioned by

blogs
1 blog
twitter
5 X users
googleplus
1 Google+ user
video
1 YouTube creator

Citations

dimensions_citation
60 Dimensions

Readers on

mendeley
38 Mendeley
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Title
Molmil: a molecular viewer for the PDB and beyond
Published in
Journal of Cheminformatics, August 2016
DOI 10.1186/s13321-016-0155-1
Pubmed ID
Authors

Gert-Jan Bekker, Haruki Nakamura, Akira R. Kinjo

Abstract

We have developed a new platform-independent web-based molecular viewer using JavaScript and WebGL. The molecular viewer, Molmil, has been integrated into several services offered by Protein Data Bank Japan and can be easily extended with new functionality by third party developers. Furthermore, the viewer can be used to load files in various formats from the user's local hard drive without uploading the data to a server. Molmil is available for all platforms supporting WebGL (e.g. Windows, Linux, iOS, Android) from http://gjbekker.github.io/molmil/. The source code is available at http://github.com/gjbekker/molmil under the LGPLv3 licence.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 3%
Japan 1 3%
Czechia 1 3%
Unknown 35 92%

Demographic breakdown

Readers by professional status Count As %
Researcher 11 29%
Student > Master 7 18%
Student > Bachelor 4 11%
Professor > Associate Professor 4 11%
Professor 3 8%
Other 7 18%
Unknown 2 5%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 10 26%
Agricultural and Biological Sciences 10 26%
Chemistry 4 11%
Engineering 3 8%
Computer Science 3 8%
Other 3 8%
Unknown 5 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 10 September 2016.
All research outputs
#2,999,611
of 24,143,470 outputs
Outputs from Journal of Cheminformatics
#294
of 891 outputs
Outputs of similar age
#50,706
of 344,375 outputs
Outputs of similar age from Journal of Cheminformatics
#5
of 14 outputs
Altmetric has tracked 24,143,470 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 891 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. This one has gotten more attention than average, scoring higher than 67% 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 344,375 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 85% of its contemporaries.
We're also able to compare this research output to 14 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 71% of its contemporaries.