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The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching

Overview of attention for article published in Journal of Cheminformatics, June 2017
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#10 of 984)
  • High Attention Score compared to outputs of the same age (95th percentile)
  • High Attention Score compared to outputs of the same age and source (88th percentile)

Mentioned by

blogs
3 blogs
twitter
54 X users
wikipedia
3 Wikipedia pages
googleplus
2 Google+ users
reddit
1 Redditor

Citations

dimensions_citation
308 Dimensions

Readers on

mendeley
262 Mendeley
citeulike
2 CiteULike
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Title
The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching
Published in
Journal of Cheminformatics, June 2017
DOI 10.1186/s13321-017-0220-4
Pubmed ID
Authors

Egon L. Willighagen, John W. Mayfield, Jonathan Alvarsson, Arvid Berg, Lars Carlsson, Nina Jeliazkova, Stefan Kuhn, Tomáš Pluskal, Miquel Rojas-Chertó, Ola Spjuth, Gilleain Torrance, Chris T. Evelo, Rajarshi Guha, Christoph Steinbeck

Abstract

The Chemistry Development Kit (CDK) is a widely used open source cheminformatics toolkit, providing data structures to represent chemical concepts along with methods to manipulate such structures and perform computations on them. The library implements a wide variety of cheminformatics algorithms ranging from chemical structure canonicalization to molecular descriptor calculations and pharmacophore perception. It is used in drug discovery, metabolomics, and toxicology. Over the last 10 years, the code base has grown significantly, however, resulting in many complex interdependencies among components and poor performance of many algorithms. We report improvements to the CDK v2.0 since the v1.2 release series, specifically addressing the increased functional complexity and poor performance. We first summarize the addition of new functionality, such atom typing and molecular formula handling, and improvement to existing functionality that has led to significantly better performance for substructure searching, molecular fingerprints, and rendering of molecules. Second, we outline how the CDK has evolved with respect to quality control and the approaches we have adopted to ensure stability, including a code review mechanism. This paper highlights our continued efforts to provide a community driven, open source cheminformatics library, and shows that such collaborative projects can thrive over extended periods of time, resulting in a high-quality and performant library. By taking advantage of community support and contributions, we show that an open source cheminformatics project can act as a peer reviewed publishing platform for scientific computing software. Graphical abstract CDK 2.0 provides new features and improved performance.

X Demographics

X Demographics

The data shown below were collected from the profiles of 54 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 262 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Canada 1 <1%
Unknown 260 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 50 19%
Student > Ph. D. Student 46 18%
Student > Master 37 14%
Student > Bachelor 19 7%
Other 11 4%
Other 33 13%
Unknown 66 25%
Readers by discipline Count As %
Chemistry 65 25%
Computer Science 26 10%
Biochemistry, Genetics and Molecular Biology 20 8%
Agricultural and Biological Sciences 19 7%
Pharmacology, Toxicology and Pharmaceutical Science 18 7%
Other 30 11%
Unknown 84 32%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 58. 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 02 March 2023.
All research outputs
#751,667
of 25,837,817 outputs
Outputs from Journal of Cheminformatics
#10
of 984 outputs
Outputs of similar age
#15,540
of 334,259 outputs
Outputs of similar age from Journal of Cheminformatics
#2
of 17 outputs
Altmetric has tracked 25,837,817 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 984 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.2. 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 334,259 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 95% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.