202 related articles for article (PubMed ID: 19618723)
1. [Quantitative structure activity relationship models based on heuristic method and gene expression programming for the prediction of the pK(a) values of sulfa drugs].
Li YQ; Si HZ; Xiao YL; Liu CH; Xia CC; Li K; Qi YX
Yao Xue Xue Bao; 2009 May; 44(5):486-90. PubMed ID: 19618723
[TBL] [Abstract][Full Text] [Related]
2. Prediction on the inhibition ratio of pyrrolidine derivatives on matrix metalloproteinase based on gene expression programming.
Li Y; You G; Jia B; Si H; Yao X
Biomed Res Int; 2014; 2014():210672. PubMed ID: 24971318
[TBL] [Abstract][Full Text] [Related]
3. Quantitative structure activity relationship model for predicting the depletion percentage of skin allergic chemical substances of glutathione.
Si H; Wang T; Zhang K; Duan YB; Yuan S; Fu A; Hu Z
Anal Chim Acta; 2007 May; 591(2):255-64. PubMed ID: 17481417
[TBL] [Abstract][Full Text] [Related]
4. Prediction of pK(a) for neutral and basic drugs based on radial basis function Neural networks and the heuristic method.
Luan F; Ma W; Zhang H; Zhang X; Liu M; Hu Z; Fan B
Pharm Res; 2005 Sep; 22(9):1454-60. PubMed ID: 16132357
[TBL] [Abstract][Full Text] [Related]
5. Predicting the activity of drugs for a group of imidazopyridine anticoccidial compounds.
Si H; Lian N; Yuan S; Fu A; Duan YB; Zhang K; Yao X
Eur J Med Chem; 2009 Oct; 44(10):4044-50. PubMed ID: 19482386
[TBL] [Abstract][Full Text] [Related]
6. QSPR modeling of flash points: an update.
Katritzky AR; Stoyanova-Slavova IB; Dobchev DA; Karelson M
J Mol Graph Model; 2007 Sep; 26(2):529-36. PubMed ID: 17532242
[TBL] [Abstract][Full Text] [Related]
7. Quantitative prediction of logk of peptides in high-performance liquid chromatography based on molecular descriptors by using the heuristic method and support vector machine.
Liu HX; Xue CX; Zhang RS; Yao XJ; Liu MC; Hu ZD; Fan BT
J Chem Inf Comput Sci; 2004; 44(6):1979-86. PubMed ID: 15554667
[TBL] [Abstract][Full Text] [Related]
8. QSPR models for the prediction of apparent volume of distribution.
Ghafourian T; Barzegar-Jalali M; Dastmalchi S; Khavari-Khorasani T; Hakimiha N; Nokhodchi A
Int J Pharm; 2006 Aug; 319(1-2):82-97. PubMed ID: 16698204
[TBL] [Abstract][Full Text] [Related]
9. Benchmarking of linear and nonlinear approaches for quantitative structure-property relationship studies of metal complexation with ionophores.
Tetko IV; Solov'ev VP; Antonov AV; Yao X; Doucet JP; Fan B; Hoonakker F; Fourches D; Jost P; Lachiche N; Varnek A
J Chem Inf Model; 2006; 46(2):808-19. PubMed ID: 16563012
[TBL] [Abstract][Full Text] [Related]
10. QSPR prediction of n-octanol/water partition coefficient for polychlorinated biphenyls.
Lü W; Chen Y; Liu M; Chen X; Hu Z
Chemosphere; 2007 Sep; 69(3):469-78. PubMed ID: 17568650
[TBL] [Abstract][Full Text] [Related]
11. Prediction of atmospheric degradation data for POPs by gene expression programming.
Luan F; Si HZ; Liu HT; Wen YY; Zhang XY
SAR QSAR Environ Res; 2008; 19(5-6):465-79. PubMed ID: 18853297
[TBL] [Abstract][Full Text] [Related]
12. The accurate QSPR models to predict the bioconcentration factors of nonionic organic compounds based on the heuristic method and support vector machine.
Liu H; Yao X; Zhang R; Liu M; Hu Z; Fan B
Chemosphere; 2006 May; 63(5):722-33. PubMed ID: 16226786
[TBL] [Abstract][Full Text] [Related]
13. Support vector machine and the heuristic method to predict the solubility of hydrocarbons in electrolyte.
Ma W; Zhang X; Luan F; Zhang H; Zhang R; Liu M; Hu Z; Fan BT
J Phys Chem A; 2005 Apr; 109(15):3485-92. PubMed ID: 16833686
[TBL] [Abstract][Full Text] [Related]
14. QSAR models for the prediction of binding affinities to human serum albumin using the heuristic method and a support vector machine.
Xue CX; Zhang RS; Liu HX; Yao XJ; Liu MC; Hu ZD; Fan BT
J Chem Inf Comput Sci; 2004; 44(5):1693-700. PubMed ID: 15446828
[TBL] [Abstract][Full Text] [Related]
15. Prediction of the melting points of fatty acids from computed molecular descriptors: a quantitative structure-property relationship study.
Guendouzi A; Mekelleche SM
Chem Phys Lipids; 2012 Jan; 165(1):1-6. PubMed ID: 22008630
[TBL] [Abstract][Full Text] [Related]
16. Quantitative structure-retention relationships for organic pollutants in biopartitioning micellar chromatography.
Xia B; Ma W; Zhang X; Fan B
Anal Chim Acta; 2007 Aug; 598(1):12-8. PubMed ID: 17693301
[TBL] [Abstract][Full Text] [Related]
17. A new topological descriptors based model for predicting intestinal epithelial transport of drugs in Caco-2 cell culture.
Marrero Ponce Y; Cabrera Pérez MA; Romero Zaldivar V; González Díaz H; Torrens F
J Pharm Pharm Sci; 2004 Jun; 7(2):186-99. PubMed ID: 15367375
[TBL] [Abstract][Full Text] [Related]
18. Quantitative structure-activity relationship models for prediction of sensory irritants (logRD50) of volatile organic chemicals.
Luan F; Ma W; Zhang X; Zhang H; Liu M; Hu Z; Fan BT
Chemosphere; 2006 May; 63(7):1142-53. PubMed ID: 16307788
[TBL] [Abstract][Full Text] [Related]
19. QSAR and classification study of 1,4-dihydropyridine calcium channel antagonists based on least squares support vector machines.
Yao X; Liu H; Zhang R; Liu M; Hu Z; Panaye A; Doucet JP; Fan B
Mol Pharm; 2005; 2(5):348-56. PubMed ID: 16196487
[TBL] [Abstract][Full Text] [Related]
20. Prediction of retention times for a large set of pesticides or toxicants based on support vector machine and the heuristic method.
Li X; Luan F; Si H; Hu Z; Liu M
Toxicol Lett; 2007 Dec; 175(1-3):136-44. PubMed ID: 18024009
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
