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Results: 1 to 20 of 149

1.

In-silico prediction of blood-brain barrier permeability.

Yan A, Liang H, Chong Y, Nie X, Yu C.

SAR QSAR Environ Res. 2013 Jan;24(1):61-74. doi: 10.1080/1062936X.2012.729224. Epub 2012 Oct 24.

PMID:
23092117
[PubMed - indexed for MEDLINE]
2.

Quantitative structure-activity relationship prediction of blood-to-brain partitioning behavior using support vector machine.

Golmohammadi H, Dashtbozorgi Z, Acree WE Jr.

Eur J Pharm Sci. 2012 Sep 29;47(2):421-9. doi: 10.1016/j.ejps.2012.06.021. Epub 2012 Jul 6.

PMID:
22771548
[PubMed - indexed for MEDLINE]
3.

Investigating the utility of momentum-space descriptors for predicting blood-brain barrier penetration.

Al-Fahemi JH, Cooper DL, Allan NL.

J Mol Graph Model. 2007 Oct;26(3):607-12. Epub 2007 Jan 14.

PMID:
17300970
[PubMed - indexed for MEDLINE]
4.

Prediction of human intestinal absorption by GA feature selection and support vector machine regression.

Yan A, Wang Z, Cai Z.

Int J Mol Sci. 2008 Oct;9(10):1961-76. doi: 10.3390/ijms9101961. Epub 2008 Oct 20.

PMID:
19325729
[PubMed]
Free PMC Article
5.

Predicting blood-brain barrier penetration of drugs using an artificial neural network.

Fu XC, Wang GP, Liang WQ, Yu QS.

Pharmazie. 2004 Feb;59(2):126-30.

PMID:
15025181
[PubMed - indexed for MEDLINE]
6.

Predicting CNS permeability of drug molecules: comparison of neural network and support vector machine algorithms.

Doniger S, Hofmann T, Yeh J.

J Comput Biol. 2002;9(6):849-64.

PMID:
12614551
[PubMed - indexed for MEDLINE]
7.

Effect of selection of molecular descriptors on the prediction of blood-brain barrier penetrating and nonpenetrating agents by statistical learning methods.

Li H, Yap CW, Ung CY, Xue Y, Cao ZW, Chen YZ.

J Chem Inf Model. 2005 Sep-Oct;45(5):1376-84.

PMID:
16180914
[PubMed - indexed for MEDLINE]
8.

In silico prediction of rhabdomyolysis of compounds by self-organizing map and support vector machine.

Hu X, Yan A.

Toxicol In Vitro. 2011 Dec;25(8):2017-24. doi: 10.1016/j.tiv.2011.08.002. Epub 2011 Aug 12.

PMID:
21856410
[PubMed - indexed for MEDLINE]
9.

Prediction of bioactivity of HIV-1 integrase ST inhibitors by multilinear regression analysis and support vector machine.

Xuan S, Wu Y, Chen X, Liu J, Yan A.

Bioorg Med Chem Lett. 2013 Mar 15;23(6):1648-55. doi: 10.1016/j.bmcl.2013.01.081. Epub 2013 Jan 27.

PMID:
23395655
[PubMed - indexed for MEDLINE]
10.

Recent advances in the prediction of blood-brain partitioning from molecular structure.

Lobell M, Molnár L, Keserü GM.

J Pharm Sci. 2003 Feb;92(2):360-70.

PMID:
12532385
[PubMed - indexed for MEDLINE]
11.

Prediction of sweetness by multilinear regression analysis and support vector machine.

Zhong M, Chong Y, Nie X, Yan A, Yuan Q.

J Food Sci. 2013 Sep;78(9):S1445-50. doi: 10.1111/1750-3841.12199. Epub 2013 Aug 5.

PMID:
23915005
[PubMed - indexed for MEDLINE]
12.

Discriminating of ATP competitive Src kinase inhibitors and decoys using self-organizing map and support vector machine.

Yan A, Hu X, Wang K, Sun J.

Mol Divers. 2013 Feb;17(1):75-83. doi: 10.1007/s11030-012-9411-0. Epub 2012 Nov 2.

PMID:
23117252
[PubMed - indexed for MEDLINE]
13.

Skin permeation rate as a function of chemical structure.

Katritzky AR, Dobchev DA, Fara DC, Hür E, Tämm K, Kurunczi L, Karelson M, Varnek A, Solov'ev VP.

J Med Chem. 2006 Jun 1;49(11):3305-14.

PMID:
16722649
[PubMed - indexed for MEDLINE]
14.

Quantitative structure and bioactivity relationship study on human acetylcholinesterase inhibitors.

Yan A, Wang K.

Bioorg Med Chem Lett. 2012 May 1;22(9):3336-42. doi: 10.1016/j.bmcl.2012.02.108. Epub 2012 Mar 11.

PMID:
22460031
[PubMed - indexed for MEDLINE]
15.

Ionization-specific QSAR models of blood-brain penetration of drugs.

Lanevskij K, Japertas P, Didziapetris R, Petrauskas A.

Chem Biodivers. 2009 Nov;6(11):2050-4. doi: 10.1002/cbdv.200900079.

PMID:
19937840
[PubMed - indexed for MEDLINE]
16.

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 30;32(15):3241-52. doi: 10.1002/jcc.21907. Epub 2011 Aug 12.

PMID:
21837634
[PubMed - indexed for MEDLINE]
17.

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. doi: 10.1111/j.1747-0285.2009.00840.x. Epub 2009 Jun 22.

PMID:
19549084
[PubMed - indexed for MEDLINE]
18.

In silico prediction of blood brain barrier permeability: an Artificial Neural Network model.

Garg P, Verma J.

J Chem Inf Model. 2006 Jan-Feb;46(1):289-97.

PMID:
16426064
[PubMed - indexed for MEDLINE]
19.

Quantitative structure and bioactivity relationship study on HCV NS5B polymerase inhibitors.

Wang M, Zhong M, Yan A, Li L, Yu C.

SAR QSAR Environ Res. 2014;25(1):1-15. doi: 10.1080/1062936X.2013.820790. Epub 2013 Nov 28.

PMID:
24283437
[PubMed - in process]
20.

Validation of topochemical models for the prediction of permeability through the blood-brain barrier.

Dureja H, Madan AK.

Acta Pharm. 2007 Dec;57(4):451-67. doi: 10.2478/v10007-007-0036-2.

PMID:
18165189
[PubMed - indexed for MEDLINE]

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