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Extended Functional Groups (EFG): An Efficient Set for Chemical Characterization and Structure-Activity Relationship Studies of Chemical Compounds
Open accessAbstract
The article describes a classification system termed “extended functional groups” (EFG), which are an extension of a set previously used by the CheckMol software, that covers in addition heterocyclic compound classes and periodic table groups. The functional groups are defined as SMARTS patterns and are available as part of the ToxAlerts tool (http://ochem.eu/alerts) of the On-line CHEmical database and Modeling (OCHEM) environment platform. The article describes the motivation and the main ideas behind this extension and demonstrates that EFG can be efficiently used to develop and interpret structure-activity relationship models.
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Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
LIBSVM: A library for support vector machines
Chang, C.-C., & Lin, C.-J. (2011) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/1961189.1961199 · Cited by 40,918
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Metadata
- Authors
- Salmina, E., Haider, N., & Tetko, I.
- Venue
- Molecules
- Publisher
- MDPI AG
- Published
- 2015-12-23
- Volume
- 21
- Issue
- 1
- Pages
- 1
- ISSN
- 1420-3049 (ISSN-L)
- OpenAlex
- W2219397146
- Cited by
- 1,041
- References
- 2
- FWCI
- 114.46
- Type
- journal article
- Language
- en
- Open access
- gold
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- Salmina, E., Haider, N., & Tetko, I. (2015). Extended Functional Groups (EFG): An Efficient Set for Chemical Characterization and Structure-Activity Relationship Studies of Chemical Compounds. Molecules. https://doi.org/10.3390/molecules21010001
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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