Ministry of Science, Technology and Development of the Republic of Serbia (Project no. 1458 - Molecular structures, chemical transformations, physicochemical characterization, pharmaceutical purity and analysis of pharmacologicaly active compounds).

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Ministry of Science, Technology and Development of the Republic of Serbia (Project no. 1458 - Molecular structures, chemical transformations, physicochemical characterization, pharmaceutical purity and analysis of pharmacologicaly active compounds).

Authors

Publications

Prediction of selectivity of α 1 -adrenergic antagonists by counterpropagation neural network (CP-ANN)

Erić, Slavica; Solmajer, Tom; Zupan, Janja; Nović, M; Oblak, M; Agbaba, Danica

(Elsevier Masson SAS, 2004) 

TY  - JOUR
AU  - Erić, Slavica
AU  - Solmajer, Tom
AU  - Zupan, Janja
AU  - Nović, M
AU  - Oblak, M
AU  - Agbaba, Danica
PY  - 2004
UR  - https://farfar.pharmacy.bg.ac.rs/handle/123456789/560
AB  - A quantitative structure-selectivity relationships of series of structurally diverse α 1 -adrenergic antagonists was performed by using counter-propagation neural network (CP-ANN). The theoretical molecular descriptors have been calculated and selected using CODESSA program. The results obtained for a highly non-congeneric set of molecules have confirmed the potential of use of CP-ANN approach in prediction of relative activity (selectivity) of α 1 -adrenergic antagonists.
PB  - Elsevier Masson SAS
T2  - Farmaco
T1  - Prediction of selectivity of α 1 -adrenergic antagonists by counterpropagation neural network (CP-ANN)
VL  - 59
IS  - 5
SP  - 389
EP  - 395
DO  - 10.1016/j.farmac.2003.12.009
ER  - 
@article{
author = "Erić, Slavica and Solmajer, Tom and Zupan, Janja and Nović, M and Oblak, M and Agbaba, Danica",
year = "2004",
abstract = "A quantitative structure-selectivity relationships of series of structurally diverse α 1 -adrenergic antagonists was performed by using counter-propagation neural network (CP-ANN). The theoretical molecular descriptors have been calculated and selected using CODESSA program. The results obtained for a highly non-congeneric set of molecules have confirmed the potential of use of CP-ANN approach in prediction of relative activity (selectivity) of α 1 -adrenergic antagonists.",
publisher = "Elsevier Masson SAS",
journal = "Farmaco",
title = "Prediction of selectivity of α 1 -adrenergic antagonists by counterpropagation neural network (CP-ANN)",
volume = "59",
number = "5",
pages = "389-395",
doi = "10.1016/j.farmac.2003.12.009"
}
Erić, S., Solmajer, T., Zupan, J., Nović, M., Oblak, M.,& Agbaba, D.. (2004). Prediction of selectivity of α 1 -adrenergic antagonists by counterpropagation neural network (CP-ANN). in Farmaco
Elsevier Masson SAS., 59(5), 389-395.
https://doi.org/10.1016/j.farmac.2003.12.009
Erić S, Solmajer T, Zupan J, Nović M, Oblak M, Agbaba D. Prediction of selectivity of α 1 -adrenergic antagonists by counterpropagation neural network (CP-ANN). in Farmaco. 2004;59(5):389-395.
doi:10.1016/j.farmac.2003.12.009 .
Erić, Slavica, Solmajer, Tom, Zupan, Janja, Nović, M, Oblak, M, Agbaba, Danica, "Prediction of selectivity of α 1 -adrenergic antagonists by counterpropagation neural network (CP-ANN)" in Farmaco, 59, no. 5 (2004):389-395,
https://doi.org/10.1016/j.farmac.2003.12.009 . .
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