The DOI matches its Crossref record; 68 of the 68 references it cites were found in a registry or an index.
The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching
Open accessAbstract
BACKGROUND: 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. RESULTS: 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. CONCLUSIONS: 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.
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Molecular representations in AI-driven drug discovery: a review and practical guide
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Self-citationArtificial Intelligence for Drug Toxicity and Safety
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Metadata
- Authors
- Willighagen, E. L., Mayfield, J. W., Alvarsson, J., Berg, A., Carlsson, L., Jeliazkova, N., Kuhn, S., Pluskal, T., Rojas-Chertó, M., Spjuth, O., Torrance, G., Evelo, C. T., Guha, R., & Steinbeck, C.
- Venue
- Journal of Cheminformatics
- Published
- 2017-06-06
- Volume
- 9
- Issue
- 1
- Pages
- 33-33
- ISSN
- 1758-2946 (ISSN-L)
- OpenAlex
- W2622236128
- Cited by
- 527
- References
- 68
- FWCI
- 32.11
- Type
- journal article
- Language
- en
- Update notices
- erratum (2017-09-20)
- Open access
- gold
- Licence
- creativecommons.org/licenses/by/4.0/ (tdm)
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- Willighagen, E. L., Mayfield, J. W., Alvarsson, J., Berg, A., Carlsson, L., Jeliazkova, N., Kuhn, S., Pluskal, T., Rojas-Chertó, M., Spjuth, O., Torrance, G., Evelo, C. T., Guha, R., & Steinbeck, C. (2017). The Chemistry Development Kit (CDK) v2.0: atom typing, depiction, molecular formulas, and substructure searching. Journal of Cheminformatics. https://doi.org/10.1186/s13321-017-0220-4
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