112 related articles for article (PubMed ID: 12768446)
1. Quantitative structure-diastereoselectivity relationships for arylsulfoxide derivatives in radical chemistry.
Zahouily M; Rayadh A; Aadil M; Zakarya D
J Mol Model; 2003 Aug; 9(4):242-7. PubMed ID: 12768446
[TBL] [Abstract][Full Text] [Related]
2. Structure-cytotoxicity relationships for a series of HEPT derivatives.
Bazoui H; Zahouily M; Sebti S; Boulajaaj S; Zakarya D
J Mol Model; 2002 Jan; 8(1):1-7. PubMed ID: 12111397
[TBL] [Abstract][Full Text] [Related]
3. QSPR study of Setschenow constants of organic compounds using MLR, ANN, and SVM analyses.
Xu J; Wang L; Wang L; Shen X; Xu W
J Comput Chem; 2011 Nov; 32(15):3241-52. PubMed ID: 21837634
[TBL] [Abstract][Full Text] [Related]
4. In silico prediction of dermal penetration rate of chemicals from their molecular structural descriptors.
Fatemi MH; Malekzadeh H
Environ Toxicol Pharmacol; 2012 Sep; 34(2):297-306. PubMed ID: 22659232
[TBL] [Abstract][Full Text] [Related]
5. Prediction of Henry's Law Constants via group-specific quantitative structure property relationships.
O'Loughlin DR; English NJ
Chemosphere; 2015 May; 127():1-9. PubMed ID: 25602194
[TBL] [Abstract][Full Text] [Related]
6. QSAR for anti-malarial activity of 2-aziridinyl and 2,3-bis(aziridinyl)-1,4-naphthoquinonyl sulfonate and acylate derivatives.
Zahouily M; Lazar M; Elmakssoudi A; Rakik J; Elaychi S; Rayadh A
J Mol Model; 2006 Mar; 12(4):398-405. PubMed ID: 16341716
[TBL] [Abstract][Full Text] [Related]
7. Prediction of gas-to-olive oil partition coefficients of organic compounds using an artificial neural network.
Golmohammadi H; Konoz E; Dashtbozorgi Z
Anal Sci; 2009 Sep; 25(9):1137-42. PubMed ID: 19745543
[TBL] [Abstract][Full Text] [Related]
8. Modeling of adipose/blood partition coefficient for environmental chemicals.
Papadaki KC; Karakitsios SP; Sarigiannis DA
Food Chem Toxicol; 2017 Dec; 110():274-285. PubMed ID: 29111282
[TBL] [Abstract][Full Text] [Related]
9. QSAR modeling of anti-invasive activity of organic compounds using structural descriptors.
Katritzky AR; Kuanar M; Dobchev DA; Vanhoecke BW; Karelson M; Parmar VS; Stevens CV; Bracke ME
Bioorg Med Chem; 2006 Oct; 14(20):6933-9. PubMed ID: 16908166
[TBL] [Abstract][Full Text] [Related]
10. Comparison of Multiple Linear Regressions and Neural Networks based QSAR models for the design of new antitubercular compounds.
Ventura C; Latino DA; Martins F
Eur J Med Chem; 2013; 70():831-45. PubMed ID: 24246731
[TBL] [Abstract][Full Text] [Related]
11. QSPR studies of impact sensitivity of nitro energetic compounds using three-dimensional descriptors.
Xu J; Zhu L; Fang D; Wang L; Xiao S; Liu L; Xu W
J Mol Graph Model; 2012 Jun; 36():10-9. PubMed ID: 22503858
[TBL] [Abstract][Full Text] [Related]
12. Structure-toxicity relationships study of a series of organophosphorus insecticides.
Zahouily M; Rhihil A; Bazoui H; Sebti S; Zakarya D
J Mol Model; 2002 May; 8(5):168-72. PubMed ID: 12858851
[TBL] [Abstract][Full Text] [Related]
13. Predictions of retention factors for some organic nucleuphiles in complexation gas chromatography.
Fatemi MH; Ghorbannezhad Z
J Chromatogr Sci; 2011; 49(6):476-81. PubMed ID: 21682998
[TBL] [Abstract][Full Text] [Related]
14. QSPR modeling of UV absorption intensities.
Katritzky AR; Slavov SH; Dobchev DA; Karelson M
J Comput Aided Mol Des; 2007 Jul; 21(7):371-7. PubMed ID: 17563860
[TBL] [Abstract][Full Text] [Related]
15. QSPR studies on soot-water partition coefficients of persistent organic pollutants by using artificial neural network.
Jiao L
Chemosphere; 2010 Jul; 80(6):671-5. PubMed ID: 20452639
[TBL] [Abstract][Full Text] [Related]
16. Predicting equilibrium vapour pressure isotope effects by using artificial neural networks or multi-linear regression - A quantitative structure property relationship approach.
Parinet J; Julien M; Nun P; Robins RJ; Remaud G; Höhener P
Chemosphere; 2015 Sep; 134():521-7. PubMed ID: 25559176
[TBL] [Abstract][Full Text] [Related]
17. QSAR for anti-HIV activity of HEPT derivatives.
Bazoui H; Zahouily M; Boulajaaj S; Sebti S; Zakarya D
SAR QSAR Environ Res; 2002 Oct; 13(6):567-77. PubMed ID: 12479372
[TBL] [Abstract][Full Text] [Related]
18. Prediction of air to liver partition coefficient for volatile organic compounds using QSAR approaches.
Dashtbozorgi Z; Golmohammadi H
Eur J Med Chem; 2010 Jun; 45(6):2182-90. PubMed ID: 20153567
[TBL] [Abstract][Full Text] [Related]
19. Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networks.
Caballero J; Fernández M
J Mol Model; 2006 Jan; 12(2):168-81. PubMed ID: 16205958
[TBL] [Abstract][Full Text] [Related]
20. Anticancer activity of selected phenolic compounds: QSAR studies using ridge regression and neural networks.
Nandi S; Vracko M; Bagchi MC
Chem Biol Drug Des; 2007 Nov; 70(5):424-36. PubMed ID: 17949360
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]