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.
163 related articles for article (PubMed ID: 16697155)
1. Boosting support vector regression in QSAR studies of bioactivities of chemical compounds. Zhou YP; Jiang JH; Lin WQ; Zou HY; Wu HL; Shen GL; Yu RQ Eur J Pharm Sci; 2006 Jul; 28(4):344-53. PubMed ID: 16697155 [TBL] [Abstract][Full Text] [Related]
2. A robust boosting regression tree with applications in quantitative structure-activity relationship studies of organic compounds. Jiao J; Tan SM; Luo RM; Zhou YP J Chem Inf Model; 2011 Apr; 51(4):816-28. PubMed ID: 21417261 [TBL] [Abstract][Full Text] [Related]
3. QSAR models for phosphoramidate prodrugs of 2'-methylcytidine as inhibitors of hepatitis C virus based on PSO boosting. Cheng Z; Zhang Y; Zhou C Chem Biol Drug Des; 2011 Dec; 78(6):948-59. PubMed ID: 21895985 [TBL] [Abstract][Full Text] [Related]
4. Prediction of toxicity of nitrobenzenes using ab initio and least squares support vector machines. Niazi A; Jameh-Bozorghi S; Nori-Shargh D J Hazard Mater; 2008 Mar; 151(2-3):603-9. PubMed ID: 17630186 [TBL] [Abstract][Full Text] [Related]
5. Comparative study of QSAR/QSPR correlations using support vector machines, radial basis function neural networks, and multiple linear regression. Yao XJ; Panaye A; Doucet JP; Zhang RS; Chen HF; Liu MC; Hu ZD; Fan BT J Chem Inf Comput Sci; 2004; 44(4):1257-66. PubMed ID: 15272833 [TBL] [Abstract][Full Text] [Related]
6. Simultaneously optimized support vector regression combined with genetic algorithm for QSAR analysis of KDR/VEGFR-2 inhibitors. Sun M; Chen J; Cai J; Cao M; Yin S; Ji M Chem Biol Drug Des; 2010 May; 75(5):494-505. PubMed ID: 20486936 [TBL] [Abstract][Full Text] [Related]
7. Feature selection and linear/nonlinear regression methods for the accurate prediction of glycogen synthase kinase-3beta inhibitory activities. Goodarzi M; Freitas MP; Jensen R J Chem Inf Model; 2009 Apr; 49(4):824-32. PubMed ID: 19338295 [TBL] [Abstract][Full Text] [Related]
8. QSAR study of malonyl-CoA decarboxylase inhibitors using GA-MLR and a new strategy of consensus modeling. Li J; Lei B; Liu H; Li S; Yao X; Liu M; Gramatica P J Comput Chem; 2008 Dec; 29(16):2636-47. PubMed ID: 18484640 [TBL] [Abstract][Full Text] [Related]
9. QSAR study of Akt/protein kinase B (PKB) inhibitors using support vector machine. Dong X; Jiang C; Hu H; Yan J; Chen J; Hu Y Eur J Med Chem; 2009 Oct; 44(10):4090-7. PubMed ID: 19497644 [TBL] [Abstract][Full Text] [Related]
10. Global, local and novel consensus quantitative structure-activity relationship studies of 4-(Phenylaminomethylene) isoquinoline-1, 3 (2H, 4H)-diones as potent inhibitors of the cyclin-dependent kinase 4. Lei B; Xi L; Li J; Liu H; Yao X Anal Chim Acta; 2009 Jun; 644(1-2):17-24. PubMed ID: 19463556 [TBL] [Abstract][Full Text] [Related]
11. Piecewise hypersphere modeling by particle swarm optimization in QSAR studies of bioactivities of chemical compounds. Lin WQ; Jiang JH; Shen Q; Wu HL; Shen GL; Yu RQ J Chem Inf Model; 2005; 45(3):535-41. PubMed ID: 15921443 [TBL] [Abstract][Full Text] [Related]
12. QSAR studies on 4-anilino-3-quinolinecarbonitriles as Src kinase inhibitors using robust PCA and both linear and nonlinear models. Sun M; Zheng Y; Wei H; Chen J; Ji M J Enzyme Inhib Med Chem; 2009 Oct; 24(5):1109-16. PubMed ID: 19555174 [TBL] [Abstract][Full Text] [Related]
14. QSAR study on 5-lipoxygenase inhibitors based on support vector machine. Niu B; Su Q; Yuan X; Lu W; Ding J Med Chem; 2012 Nov; 8(6):1108-16. PubMed ID: 22779798 [TBL] [Abstract][Full Text] [Related]
15. Determining the validity of a QSAR model--a classification approach. Guha R; Jurs PC J Chem Inf Model; 2005; 45(1):65-73. PubMed ID: 15667130 [TBL] [Abstract][Full Text] [Related]
16. Molecular connectivity indices for predicting bioactivities of substituted nitrobenzene and aniline compounds. Lin KH; Jaw CG; Yen JH; Wang YS Ecotoxicol Environ Saf; 2009 Oct; 72(7):1942-9. PubMed ID: 19423164 [TBL] [Abstract][Full Text] [Related]
17. QSAR study of heparanase inhibitors activity using artificial neural networks and Levenberg-Marquardt algorithm. Jalali-Heravi M; Asadollahi-Baboli M; Shahbazikhah P Eur J Med Chem; 2008 Mar; 43(3):548-56. PubMed ID: 17602800 [TBL] [Abstract][Full Text] [Related]
18. Exploring QSAR for substituted 2-sulfonyl-phenyl-indol derivatives as potent and selective COX-2 inhibitors using different chemometrics tools. Khoshneviszadeh M; Edraki N; Miri R; Hemmateenejad B Chem Biol Drug Des; 2008 Dec; 72(6):564-74. PubMed ID: 19090923 [TBL] [Abstract][Full Text] [Related]
19. Exploration of QSAR modelling techniques and their combination to rationalize the physicochemical characters of nitrophenyl derivatives towards aldose reductase inhibition. Soni LK; Gupta AK; Kaskhedikar SG J Enzyme Inhib Med Chem; 2009 Aug; 24(4):1002-7. PubMed ID: 19514863 [TBL] [Abstract][Full Text] [Related]
20. QSAR study of PETT derivatives as potent HIV-1 reverse transcriptase inhibitors. Sabet R; Fassihi A; Moeinifard B J Mol Graph Model; 2009 Sep; 28(2):146-55. PubMed ID: 19570701 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]