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Items: 1 to 20 of 216

1.

Modeling of human cytochrome p450-mediated drug metabolism using unsupervised machine learning approach.

Korolev D, Balakin KV, Nikolsky Y, Kirillov E, Ivanenkov YA, Savchuk NP, Ivashchenko AA, Nikolskaya T.

J Med Chem. 2003 Aug 14;46(17):3631-43.

PMID:
12904067
2.

Kohonen maps for prediction of binding to human cytochrome P450 3A4.

Balakin KV, Ekins S, Bugrim A, Ivanenkov YA, Korolev D, Nikolsky YV, Skorenko AV, Ivashchenko AA, Savchuk NP, Nikolskaya T.

Drug Metab Dispos. 2004 Oct;32(10):1183-9.

3.

Quantitative structure-metabolism relationship modeling of metabolic N-dealkylation reaction rates.

Balakin KV, Ekins S, Bugrim A, Ivanenkov YA, Korolev D, Nikolsky YV, Ivashchenko AA, Savchuk NP, Nikolskaya T.

Drug Metab Dispos. 2004 Oct;32(10):1111-20.

4.

Designing better drugs: predicting cytochrome P450 metabolism.

de Groot MJ.

Drug Discov Today. 2006 Jul;11(13-14):601-6.

PMID:
16793528
5.

Considerations and recent advances in QSAR models for cytochrome P450-mediated drug metabolism prediction.

Li H, Sun J, Fan X, Sui X, Zhang L, Wang Y, He Z.

J Comput Aided Mol Des. 2008 Nov;22(11):843-55. doi: 10.1007/s10822-008-9225-4. Review.

PMID:
18574695
6.

Virtual screening for cytochromes p450: successes of machine learning filters.

Burton J, Ijjaali I, Petitet F, Michel A, Vercauteren DP.

Comb Chem High Throughput Screen. 2009 May;12(4):369-82. Review.

PMID:
19442071
7.

[Cytochrome P450 isoenzymes in metabolism of endo- and exogenic compounds].

Wiśniewska A, Mazerska Z.

Postepy Biochem. 2009;55(3):259-71. Review. Polish.

PMID:
19928582
8.

Molecular modeling of human cytochrome P450-substrate interactions.

Lewis DF.

Drug Metab Rev. 2002 Feb-May;34(1-2):55-67. Review.

PMID:
11996012
9.

Machine learning techniques for in silico modeling of drug metabolism.

Fox T, Kriegl JM.

Curr Top Med Chem. 2006;6(15):1579-91. Review.

PMID:
16918470
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 Nov-Dec;43(6):2019-24.

PMID:
14632453
11.

Cytochromes P450 in the bioactivation of chemicals.

Ioannides C, Lewis DF.

Curr Top Med Chem. 2004;4(16):1767-88. Review.

PMID:
15579107
13.

Classification of substrates and inhibitors of P-glycoprotein using unsupervised machine learning approach.

Wang YH, Li Y, Yang SL, Yang L.

J Chem Inf Model. 2005 May-Jun;45(3):750-7.

PMID:
15921464
16.

Classification of highly unbalanced CYP450 data of drugs using cost sensitive machine learning techniques.

Eitrich T, Kless A, Druska C, Meyer W, Grotendorst J.

J Chem Inf Model. 2007 Jan-Feb;47(1):92-103.

PMID:
17238253
17.

Database mining applied to central nervous system (CNS) activity.

Pintore M, Taboureau O, Ros F, Chrétien JR.

Eur J Med Chem. 2001 Apr;36(4):349-59.

PMID:
11461760
18.

MetaSite: understanding metabolism in human cytochromes from the perspective of the chemist.

Cruciani G, Carosati E, De Boeck B, Ethirajulu K, Mackie C, Howe T, Vianello R.

J Med Chem. 2005 Nov 3;48(22):6970-9.

PMID:
16250655
19.

Computational models for predicting interactions with cytochrome p450 enzyme.

Arimoto R.

Curr Top Med Chem. 2006;6(15):1609-18. Review.

PMID:
16918472
20.

Comprehensive computational assessment of ADME properties using mapping techniques.

Balakin KV, Ivanenkov YA, Savchuk NP, Ivashchenko AA, Ekins S.

Curr Drug Discov Technol. 2005 Jun;2(2):99-113.

PMID:
16472234

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