362 related articles for article (PubMed ID: 14632457)
1. Drug discovery using support vector machines. The case studies of drug-likeness, agrochemical-likeness, and enzyme inhibition predictions.
Zernov VV; Balakin KV; Ivaschenko AA; Savchuk NP; Pletnev IV
J Chem Inf Comput Sci; 2003; 43(6):2048-56. PubMed ID: 14632457
[TBL] [Abstract][Full Text] [Related]
2. Comparison of support vector machine and artificial neural network systems for drug/nondrug classification.
Byvatov E; Fechner U; Sadowski J; Schneider G
J Chem Inf Comput Sci; 2003; 43(6):1882-9. PubMed ID: 14632437
[TBL] [Abstract][Full Text] [Related]
3. Application of support vector machine (SVM) for prediction toxic activity of different data sets.
Zhao CY; Zhang HX; Zhang XY; Liu MC; Hu ZD; Fan BT
Toxicology; 2006 Jan; 217(2-3):105-19. PubMed ID: 16213080
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. Classifying "kinase inhibitor-likeness" by using machine-learning methods.
Briem H; Günther J
Chembiochem; 2005 Mar; 6(3):558-66. PubMed ID: 15696507
[TBL] [Abstract][Full Text] [Related]
6. 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]
7. In silico log P prediction for a large data set with support vector machines, radial basis neural networks and multiple linear regression.
Chen HF
Chem Biol Drug Des; 2009 Aug; 74(2):142-7. PubMed ID: 19549084
[TBL] [Abstract][Full Text] [Related]
8. Drug/nondrug classification using Support Vector Machines with various feature selection strategies.
Korkmaz S; Zararsiz G; Goksuluk D
Comput Methods Programs Biomed; 2014 Nov; 117(2):51-60. PubMed ID: 25224081
[TBL] [Abstract][Full Text] [Related]
9. Prediction of P-glycoprotein substrates by a support vector machine approach.
Xue Y; Yap CW; Sun LZ; Cao ZW; Wang JF; Chen YZ
J Chem Inf Comput Sci; 2004; 44(4):1497-505. PubMed ID: 15272858
[TBL] [Abstract][Full Text] [Related]
10. Comparison of linear and nonlinear classification algorithms for the prediction of drug and chemical metabolism by human UDP-glucuronosyltransferase isoforms.
Sorich MJ; Miners JO; McKinnon RA; Winkler DA; Burden FR; Smith PA
J Chem Inf Comput Sci; 2003; 43(6):2019-24. PubMed ID: 14632453
[TBL] [Abstract][Full Text] [Related]
11. Prediction of acetylcholinesterase inhibitors and characterization of correlative molecular descriptors by machine learning methods.
Lv W; Xue Y
Eur J Med Chem; 2010 Mar; 45(3):1167-72. PubMed ID: 20053484
[TBL] [Abstract][Full Text] [Related]
12. Prediction of factor Xa inhibitors by machine learning methods.
Lin HH; Han LY; Yap CW; Xue Y; Liu XH; Zhu F; Chen YZ
J Mol Graph Model; 2007 Sep; 26(2):505-18. PubMed ID: 17418603
[TBL] [Abstract][Full Text] [Related]
13. Predictive activity profiling of drugs by topological-fragment-spectra-based support vector machines.
Kawai K; Fujishima S; Takahashi Y
J Chem Inf Model; 2008 Jun; 48(6):1152-60. PubMed ID: 18533712
[TBL] [Abstract][Full Text] [Related]
14. Proteochemometric recognition of stable kinase inhibition complexes using topological autocorrelation and support vector machines.
Fernandez M; Ahmad S; Sarai A
J Chem Inf Model; 2010 Jun; 50(6):1179-88. PubMed ID: 20524632
[TBL] [Abstract][Full Text] [Related]
15. Prediction of fungicidal activities of rice blast disease based on least-squares support vector machines and project pursuit regression.
Du H; Wang J; Hu Z; Yao X; Zhang X
J Agric Food Chem; 2008 Nov; 56(22):10785-92. PubMed ID: 18950187
[TBL] [Abstract][Full Text] [Related]
16. Prediction of genotoxicity of chemical compounds by statistical learning methods.
Li H; Ung CY; Yap CW; Xue Y; Li ZR; Cao ZW; Chen YZ
Chem Res Toxicol; 2005 Jun; 18(6):1071-80. PubMed ID: 15962942
[TBL] [Abstract][Full Text] [Related]
17. A novel approach using pharmacophore ensemble/support vector machine (PhE/SVM) for prediction of hERG liability.
Leong MK
Chem Res Toxicol; 2007 Feb; 20(2):217-26. PubMed ID: 17261034
[TBL] [Abstract][Full Text] [Related]
18. Spline-fitting with a genetic algorithm: a method for developing classification structure-activity relationships.
Sutherland JJ; O'Brien LA; Weaver DF
J Chem Inf Comput Sci; 2003; 43(6):1906-15. PubMed ID: 14632439
[TBL] [Abstract][Full Text] [Related]
19. "In-house likeness": comparison of large compound collections using artificial neural networks.
Muresan S; Sadowski J
J Chem Inf Model; 2005; 45(4):888-93. PubMed ID: 16045282
[TBL] [Abstract][Full Text] [Related]
20. Learning the drug target-likeness of a protein.
Xu H; Xu H; Lin M; Wang W; Li Z; Huang J; Chen Y; Chen X
Proteomics; 2007 Dec; 7(23):4255-63. PubMed ID: 17963289
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]