The DOI matches its Crossref record; 100 of the 100 references it cites were found in a registry or an index.
Principles of QSAR Modeling: Comments and Suggestions From Personal Experience
Open accessAbstract
At the end of her academic career, the author summarizes the main aspects of QSAR modeling, giving comments and suggestions according to her 23 years' experience in QSAR research on environmental topics. The focus is mainly on Multiple Linear Regression, particularly Ordinary Least Squares, using a Genetic Algorithm for variable selection from various theoretical molecular descriptors, but the comments can be useful also for other QSAR methods. The need for rigorous validation, also external, and for applicability domain check to guarantee predictivity and reliability of QSAR models is particularly highlighted. The commented approach is the “predictive” one, based on chemometrics, and is usefully applied to the prioritization of environmental pollutants. All the discussed points and the author's ideas are implemented in the software QSARINS, as a legacy to the QSAR community.
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Cites
A concordance correlation coefficient to evaluate reproducibility.
Lin, L. I.-K. (1989) · Biometrics · doi:10.2307/2532051 · Cited by 8,785
Chai, T., & Draxler, R. R. (2014) · Geoscientific Model Development · doi:10.5194/gmd-7-1247-2014 · Cited by 7,178 · cited 1×
“The different quality of these two parameters is commented in the literature (Chai & Draxler, 2014; Roy et al., 2016).”
BackgroundHandbook of Molecular Descriptors
Todeschini, R., & Consonni, V. (2000) · Methods and Principles in Medicinal Chemistry · doi:10.1002/9783527613106 · Cited by 4,107 · cited 1×
“A comprehensive analysis of thousands of molecular descriptors was done by Todeschini & Consonni in their Handbooks (Todeschini & Consonni, 2000, 2008).”
MethodGolbraikh, A., & Tropsha, A. (2002) · Journal of Molecular Graphics and Modelling · doi:10.1016/s1093-3263(01)00123-1 · Cited by 3,735 · cited 5×
“…each developed model are: a) to carefully verify the statistical predictivity of QSAR models by their validation (as requested by OECD principle 4), also externally on new chemicals, b) to scramble the response (Y scrambling) (Eriksson et al, 2003; Golbraikh & Tropsha, 2002; Tropsha et al. 2003).”
BackgroundMethodInfluentialPaDEL‐descriptor: An open source software to calculate molecular descriptors and fingerprints
Yap, C. W. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21707 · Cited by 2,962
Hawkins, D. M. (2004) · Journal of Chemical Information and Computer Sciences · doi:10.1021/ci0342472 · Cited by 2,522
Principles of QSAR models validation: internal and external
Gramatica, P. (2007) · QSAR & Combinatorial Science · doi:10.1002/qsar.200610151 · Cited by 2,208
Self-citationTropsha, A., Gramatica, P., & Gombar, V. K. (2003) · QSAR & Combinatorial Science · doi:10.1002/qsar.200390007 · Cited by 2,188
Self-citationQSAR Modeling: Where have you been? Where are you going to?
Cherkasov, A., Muratov, E. N., Fourches, D., Varnek, A., Baskin, I. I., Cronin, M., Dearden, J., Gramatica, P., Martin, Y. C., Todeschini, R., et al. (2014) · Journal of Medicinal Chemistry · doi:10.1021/jm4004285 · Cited by 2,164
Self-citationBest Practices for QSAR Model Development, Validation, and Exploitation
Tropsha, A. (2010) · Molecular Informatics · doi:10.1002/minf.201000061 · Cited by 2,024
Metadata
- Authors
- Gramatica, P.
- Venue
- International Journal of Quantitative Structure-Property Relationships
- Publisher
- IGI Global
- Published
- 2020-07-01
- Volume
- 5
- Issue
- 3
- Pages
- 61-97
- ISSN
- 2379-7479 (ISSN-L)
- 2379-7487
- OpenAlex
- W3019103367
- Cited by
- 258
- References
- 100
- FWCI
- 16.68
- Type
- journal article
- Language
- ng
- Open access
- hybrid
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