205 related articles for article (PubMed ID: 16426043)
21. 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]
22. 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]
23. 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]
24. Jackknife-based selection of Gram-Schmidt orthogonalized descriptors in QSAR.
Kompany-Zareh M; Omidikia N
J Chem Inf Model; 2010 Dec; 50(12):2055-66. PubMed ID: 21069957
[TBL] [Abstract][Full Text] [Related]
25. Gas chromatographic quantitative structure-retention relationships of trimethylsilylated anabolic androgenic steroids by multiple linear regression and partial least squares.
Fragkaki AG; Tsantili-Kakoulidou A; Angelis YS; Koupparis M; Georgakopoulos C
J Chromatogr A; 2009 Nov; 1216(47):8404-20. PubMed ID: 19836752
[TBL] [Abstract][Full Text] [Related]
26. QSAR study for the soybean 15-lipoxygenase inhibitory activity of organosulfur compounds derived from the essential oil of garlic.
Camargo AB; Marchevsky E; Luco JM
J Agric Food Chem; 2007 Apr; 55(8):3096-103. PubMed ID: 17367159
[TBL] [Abstract][Full Text] [Related]
27. Optimized block-wise variable combination by particle swarm optimization for partial least squares modeling in quantitative structure-activity relationship studies.
Lin WQ; Jiang JH; Shen Q; Shen GL; Yu RQ
J Chem Inf Model; 2005; 45(2):486-93. PubMed ID: 15807514
[TBL] [Abstract][Full Text] [Related]
28. QSAR study of isatin analogues as in vitro anti-cancer agents.
Sabet R; Mohammadpour M; Sadeghi A; Fassihi A
Eur J Med Chem; 2010 Mar; 45(3):1113-8. PubMed ID: 20056518
[TBL] [Abstract][Full Text] [Related]
29. 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]
30. On the physical interpretation of QSAR models.
Stanton DT
J Chem Inf Comput Sci; 2003; 43(5):1423-33. PubMed ID: 14502475
[TBL] [Abstract][Full Text] [Related]
31. 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]
32. Quantitative structure/property relationship analysis on aqueous solubility using genetic algorithm-combined partial least squares method.
Wanchana S; Yamashita F; Hashida M
Pharmazie; 2002 Feb; 57(2):127-9. PubMed ID: 11878188
[TBL] [Abstract][Full Text] [Related]
33. QSAR study on tetrahydroquinoline analogues as plasmodium protein farnesyltransferase inhibitors: a comparison of rationales of malarial and mammalian enzyme inhibitory activities for selectivity.
Gupta MK; Prabhakar YS
Eur J Med Chem; 2008 Dec; 43(12):2751-67. PubMed ID: 18329140
[TBL] [Abstract][Full Text] [Related]
34. Description of the electronic structure of organic chemicals using semiempirical and ab initio methods for development of toxicological QSARs.
Netzeva TI; Aptula AO; Benfenati E; Cronin MT; Gini G; Lessigiarska I; Maran U; Vracko M; Schüürmann G
J Chem Inf Model; 2005; 45(1):106-14. PubMed ID: 15667135
[TBL] [Abstract][Full Text] [Related]
35. Quantitative HPLC analysis of two key flavonoids and inhibitory activities against aldose reductase from different parts of the Korean thistle, Cirsium maackii.
Jung HA; Kim YS; Choi JS
Food Chem Toxicol; 2009 Nov; 47(11):2790-7. PubMed ID: 19733610
[TBL] [Abstract][Full Text] [Related]
36. Artificial neural network-based drug design for diabetes mellitus using flavonoids.
Patra JC; Chua BH
J Comput Chem; 2011 Mar; 32(4):555-67. PubMed ID: 20806262
[TBL] [Abstract][Full Text] [Related]
37. Combinatorial protocol in multiple linear regression/partial least-squares directed rationale for the caspase-3 inhibition activity of isoquinoline-1,3,4-trione derivatives.
Sharma BK; Pilania P; Singh P; Prabhakar YS
SAR QSAR Environ Res; 2010 Jan; 21(1):169-85. PubMed ID: 20373219
[TBL] [Abstract][Full Text] [Related]
38. Quantitative structure-activity relationship study of aromatic inhibitors against rat lens aldose reductase activity using variable selections.
Jung M; Lee Y; Shim M; Lim E; Lee EJ; Lee HC
Med Chem; 2013 May; 9(3):410-9. PubMed ID: 22931492
[TBL] [Abstract][Full Text] [Related]
39. Topological descriptors in modeling the agonistic activity of human A3 adenosine receptor ligands: the derivatives of 2-chloro-N(6)-substituted-4'-thioadenosine-5'-uronamide.
Sharma S; Sharma BK; Sharma SK; Singh P; Prabhakar YS
Eur J Med Chem; 2009 Apr; 44(4):1377-82. PubMed ID: 18973967
[TBL] [Abstract][Full Text] [Related]
40. Comparative multiple quantitative structure-retention relationships modeling of gas chromatographic retention time of essential oils using multiple linear regression, principal component regression, and partial least squares techniques.
Qin LT; Liu SS; Liu HL; Tong J
J Chromatogr A; 2009 Jul; 1216(27):5302-12. PubMed ID: 19486989
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]