These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
207 related articles for article (PubMed ID: 18261511)
1. Application of the modelling power approach to variable subset selection for GA-PLS QSAR models. Sagrado S; Cronin MT Anal Chim Acta; 2008 Feb; 609(2):169-74. PubMed ID: 18261511 [TBL] [Abstract][Full Text] [Related]
2. Partial least squares modeling and genetic algorithm optimization in quantitative structure-activity relationships. Hasegawa K; Funatsu K SAR QSAR Environ Res; 2000; 11(3-4):189-209. PubMed ID: 10969871 [TBL] [Abstract][Full Text] [Related]
3. Quantitative structure-activity relationship modeling of dopamine D(1) antagonists using comparative molecular field analysis, genetic algorithms-partial least-squares, and K nearest neighbor methods. Hoffman B; Cho SJ; Zheng W; Wyrick S; Nichols DE; Mailman RB; Tropsha A J Med Chem; 1999 Aug; 42(17):3217-26. PubMed ID: 10464009 [TBL] [Abstract][Full Text] [Related]
4. Improvement of multivariate image analysis applied to quantitative structure-activity relationship (QSAR) analysis by using wavelet-principal component analysis ranking variable selection and least-squares support vector machine regression: QSAR study of checkpoint kinase WEE1 inhibitors. Cormanich RA; Goodarzi M; Freitas MP Chem Biol Drug Des; 2009 Feb; 73(2):244-52. PubMed ID: 19207427 [TBL] [Abstract][Full Text] [Related]
5. Exploration of linear modelling techniques and their combination with multivariate adaptive regression splines to predict gastro-intestinal absorption of drugs. Deconinck E; Coomans D; Vander Heyden Y J Pharm Biomed Anal; 2007 Jan; 43(1):119-30. PubMed ID: 16859855 [TBL] [Abstract][Full Text] [Related]
6. Diagnostic tools to determine the quality of "transparent" regression-based QSARs: the "modelling power" plot. Sagrado S; Cronin MT J Chem Inf Model; 2006; 46(3):1523-32. PubMed ID: 16711772 [TBL] [Abstract][Full Text] [Related]
7. A self-adaptive genetic algorithm-artificial neural network algorithm with leave-one-out cross validation for descriptor selection in QSAR study. Wu J; Mei J; Wen S; Liao S; Chen J; Shen Y J Comput Chem; 2010 Jul; 31(10):1956-68. PubMed ID: 20512843 [TBL] [Abstract][Full Text] [Related]
8. Application of genetic algorithm-kernel partial least square as a novel nonlinear feature selection method: activity of carbonic anhydrase II inhibitors. Jalali-Heravi M; Kyani A Eur J Med Chem; 2007 May; 42(5):649-59. PubMed ID: 17316919 [TBL] [Abstract][Full Text] [Related]
9. Retention prediction of peptides based on uninformative variable elimination by partial least squares. Put R; Daszykowski M; Baczek T; Vander Heyden Y J Proteome Res; 2006 Jul; 5(7):1618-25. PubMed ID: 16823969 [TBL] [Abstract][Full Text] [Related]
10. Exploring QSARs for inhibitory activity of non-peptide HIV-1 protease inhibitors by GA-PLS and GA-SVM. Deeb O; Goodarzi M Chem Biol Drug Des; 2010 May; 75(5):506-14. PubMed ID: 20486937 [TBL] [Abstract][Full Text] [Related]
11. Comparison of MLR, PLS and GA-MLR in QSAR analysis. Saxena AK; Prathipati P SAR QSAR Environ Res; 2003; 14(5-6):433-45. PubMed ID: 14758986 [TBL] [Abstract][Full Text] [Related]
12. Modified particle swarm optimization algorithm for variable selection in MLR and PLS modeling: QSAR studies of antagonism of angiotensin II antagonists. Shen Q; Jiang JH; Jiao CX; Shen GL; Yu RQ Eur J Pharm Sci; 2004 Jun; 22(2-3):145-52. PubMed ID: 15158899 [TBL] [Abstract][Full Text] [Related]
13. Genetic algorithm optimisation combined with partial least squares regression and mutual information variable selection procedures in near-infrared quantitative analysis of cotton-viscose textiles. Durand A; Devos O; Ruckebusch C; Huvenne JP Anal Chim Acta; 2007 Jul; 595(1-2):72-9. PubMed ID: 17605985 [TBL] [Abstract][Full Text] [Related]
14. Multi-objective genetic algorithm-based sample selection for partial least squares model building with applications to near-infrared spectroscopic data. Shinzawa H; Li B; Nakagawa T; Maruo K; Ozaki Y Appl Spectrosc; 2006 Jun; 60(6):631-40. PubMed ID: 16808864 [TBL] [Abstract][Full Text] [Related]
15. Improved variable reduction in partial least squares modelling based on predictive-property-ranked variables and adaptation of partial least squares complexity. Andries JP; Vander Heyden Y; Buydens LM Anal Chim Acta; 2011 Oct; 705(1-2):292-305. PubMed ID: 21962372 [TBL] [Abstract][Full Text] [Related]
16. Modeling calcium channel antagonistic activity of dihydropyridine derivatives using QTMS indices analyzed by GA-PLS and PC-GA-PLS. Mohajeri A; Hemmateenejad B; Mehdipour A; Miri R J Mol Graph Model; 2008 Apr; 26(7):1057-65. PubMed ID: 17959402 [TBL] [Abstract][Full Text] [Related]
17. The impact of variable selection on the modelling of oestrogenicity. Ghafourian T; Cronin MT SAR QSAR Environ Res; 2005; 16(1-2):171-90. PubMed ID: 15844449 [TBL] [Abstract][Full Text] [Related]