The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Application of Associative Neural Networks for Prediction of Lipophilicity in ALOGPS 2.1 Program
Abstract
This article provides a systematic study of several important parameters of the Associative Neural Network (ASNN), such as the number of networks in the ensemble, distance measures, neighbor functions, selection of smoothing parameters, and strategies for the user-training feature of the algorithm. The performance of the different methods is assessed with several training/test sets used to predict lipophilicity of chemical compounds. The Spearman rank-order correlation coefficient and Parzen-window regression methods provide the best performance of the algorithm. If additional user data is available, an improved prediction of lipophilicity of chemicals up to 2-5 times can be calculated when the appropriate smoothing parameters for the neural network are selected. The detected best combinations of parameters and strategies are implemented in the ALOGPS 2.1 program that is publicly available at http://www.vcclab.org/lab/alogps.
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Neural Networks for Pattern Recognition
Bishop, C. M. (1995) · doi:10.1093/oso/9780198538493.001.0001 · Cited by 12,287
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Thorpe, S., Fize, D., & Marlot, C. (1996) · Nature · doi:10.1038/381520a0 · Cited by 3,538
Cited by
Rayne, S., & Forest, K. (2009) · Journal of Environmental Science and Health, Part A · doi:10.1080/10934520903139811 · Cited by 475
A solvent having switchable hydrophilicity
Jessop, P. G., Phan, L., Carrier, A., Robinson, S., Dürr, C. J., & Harjani, J. R. (2010) · Green Chemistry · doi:10.1039/b926885e · Cited by 329
Tertiary amine solvents having switchable hydrophilicity
Jessop, P. G., Kozycz, L., Rahami, Z. G., Schoenmakers, D., Boyd, A. R., Wechsler, D., & Holland, A. M. (2011) · Green Chemistry · doi:10.1039/c0gc00806k · Cited by 260
Design and evaluation of switchable-hydrophilicity solvents
Vanderveen, J. R., Durelle, J., & Jessop, P. G. (2014) · Green Chem. · doi:10.1039/c3gc42164c · Cited by 251
A renaissance of neural networks in drug discovery
Baskin, I. I., Winkler, D., & Tetko, I. V. (2016) · Expert Opinion on Drug Discovery · doi:10.1080/17460441.2016.1201262 · Cited by 235
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Metadata
- Authors
- Tetko, I. V., & Tanchuk, V. Y.
- Venue
- Journal of Chemical Information and Computer Sciences
- Publisher
- American Chemical Society (ACS)
- Published
- 2002-08-09
- Volume
- 42
- Issue
- 5
- Pages
- 1136-1145
- ISSN
- 0095-2338 (ISSN-L)
- OpenAlex
- W1541037889
- Cited by
- 617
- References
- 2
- FWCI
- 13.28
- Type
- journal article
- Language
- en
- Open access
- closed
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