Pretražite po imenu i prezimenu autora, mentora, urednika, prevoditelja

Napredna pretraga

Pregled bibliografske jedinice broj: 312157

Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones


Bašic, Ivan; Nadramija, Damir; Flajšlik, Mario; Amić, Dragan; Lučić, Bono
Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones // Special Volume of the American Institute of Physics (AIP) - Conference Proceedings of ICCMSE 2007 / Simos, Theodore (ur.).
Melville (NY): American Institute of Physics (AIP), 2007. str. 521-523 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)


CROSBI ID: 312157 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones

Autori
Bašic, Ivan ; Nadramija, Damir ; Flajšlik, Mario ; Amić, Dragan ; Lučić, Bono

Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni

Izvornik
Special Volume of the American Institute of Physics (AIP) - Conference Proceedings of ICCMSE 2007 / Simos, Theodore - Melville (NY) : American Institute of Physics (AIP), 2007, 521-523

Skup
International Conference of Computational Methods in Sciences and Engineering 2007

Mjesto i datum
Krf, Grčka, 25.09.2007. - 30.09.2007

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
HEPT derivatives ; anti-HIV activity ; QSAR models ; descriptor selection ; multivariate regression ; artificial neural networks ; non-linear relationships

Sažetak
Several quantitative structure-activity studies for this data set containing 107 HEPT derivatives have been performed since 1997, using the same set of molecules by (more or less) different classes of molecular descriptors. Multivariate Regression (MR) and Artificial Neural Network (ANN) models were developed and in each study the authors concluded that ANN models are superior to MR ones. We re-calculated multivariate regression models for this set of molecules using the same set of descriptors, and compared our results with the previous ones. Two main reasons for overestimation of the quality of the ANN models in previous studies comparing with MR models are: (1) wrong calculation of leave-one-out (LOO) cross-validated (CV) correlation coefficient for MR models in Luco et al., J. Chem. Inf. Comput. Sci. 37 392-401(1997), and (2) incorrect estimation/interpretation of leave-one-out (LOO) cross-validated and predictive performance and power of ANN models. More precise and more fair comparison of fit and LOO CV statistical parameters shows that MR models are more stable. In addition, MR models are much simpler than ANN ones. For real testing the predictive performance of both classes of models we need more HEPT derivatives, because all ANN models that presented results for external set of molecules used experimental values in optimization of modeling procedure and model parameters.

Izvorni jezik
Engleski

Znanstvena područja
Kemija



POVEZANOST RADA


Projekti:
MZOS-098-1770495-2919 - Razvoj metoda za modeliranje svojstava bioaktivnih molekula i proteina (Lučić, Bono, MZOS ) ( CroRIS)

Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb,
Fakultet agrobiotehničkih znanosti Osijek,
Institut "Ruđer Bošković", Zagreb

Profili:

Avatar Url Bono Lučić (autor)

Avatar Url Damir Nadramija (autor)

Avatar Url Dragan Amić (autor)

Avatar Url Ivan Bašic (autor)


Citiraj ovu publikaciju:

Bašic, Ivan; Nadramija, Damir; Flajšlik, Mario; Amić, Dragan; Lučić, Bono
Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones // Special Volume of the American Institute of Physics (AIP) - Conference Proceedings of ICCMSE 2007 / Simos, Theodore (ur.).
Melville (NY): American Institute of Physics (AIP), 2007. str. 521-523 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
Bašic, I., Nadramija, D., Flajšlik, M., Amić, D. & Lučić, B. (2007) Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones. U: Simos, T. (ur.)Special Volume of the American Institute of Physics (AIP) - Conference Proceedings of ICCMSE 2007.
@article{article, author = {Ba\v{s}ic, Ivan and Nadramija, Damir and Flaj\v{s}lik, Mario and Ami\'{c}, Dragan and Lu\v{c}i\'{c}, Bono}, editor = {Simos, T.}, year = {2007}, pages = {521-523}, keywords = {HEPT derivatives, anti-HIV activity, QSAR models, descriptor selection, multivariate regression, artificial neural networks, non-linear relationships}, title = {Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones}, keyword = {HEPT derivatives, anti-HIV activity, QSAR models, descriptor selection, multivariate regression, artificial neural networks, non-linear relationships}, publisher = {American Institute of Physics (AIP)}, publisherplace = {Krf, Gr\v{c}ka} }
@article{article, author = {Ba\v{s}ic, Ivan and Nadramija, Damir and Flaj\v{s}lik, Mario and Ami\'{c}, Dragan and Lu\v{c}i\'{c}, Bono}, editor = {Simos, T.}, year = {2007}, pages = {521-523}, keywords = {HEPT derivatives, anti-HIV activity, QSAR models, descriptor selection, multivariate regression, artificial neural networks, non-linear relationships}, title = {Modeling anti-HIV activity of HEPT derivatives revisited. Multiregression models are not inferior ones}, keyword = {HEPT derivatives, anti-HIV activity, QSAR models, descriptor selection, multivariate regression, artificial neural networks, non-linear relationships}, publisher = {American Institute of Physics (AIP)}, publisherplace = {Krf, Gr\v{c}ka} }




Contrast
Increase Font
Decrease Font
Dyslexic Font