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Items: 1 to 20 of 152

1.

Drug-target interaction prediction by learning from local information and neighbors.

Mei JP, Kwoh CK, Yang P, Li XL, Zheng J.

Bioinformatics. 2013 Jan 15;29(2):238-45. doi: 10.1093/bioinformatics/bts670. Epub 2012 Nov 17.

PMID:
23162055
2.

Supervised prediction of drug-target interactions using bipartite local models.

Bleakley K, Yamanishi Y.

Bioinformatics. 2009 Sep 15;25(18):2397-403. doi: 10.1093/bioinformatics/btp433. Epub 2009 Jul 15.

3.

[Prediction of network drug target based on improved model of bipartite graph valuation].

Liu X, Lu P, Zuo X, Chen J, Yang H, Yang Y, Gao Y.

Zhongguo Zhong Yao Za Zhi. 2012 Jan;37(2):125-9. Chinese.

PMID:
22737836
4.

Gaussian interaction profile kernels for predicting drug-target interaction.

van Laarhoven T, Nabuurs SB, Marchiori E.

Bioinformatics. 2011 Nov 1;27(21):3036-43. doi: 10.1093/bioinformatics/btr500. Epub 2011 Sep 4.

PMID:
21893517
5.

Predicting drug-target interactions from chemical and genomic kernels using Bayesian matrix factorization.

Gönen M.

Bioinformatics. 2012 Sep 15;28(18):2304-10. doi: 10.1093/bioinformatics/bts360. Epub 2012 Jun 23.

PMID:
22730431
6.

Drug-target interaction prediction from chemical, genomic and pharmacological data in an integrated framework.

Yamanishi Y, Kotera M, Kanehisa M, Goto S.

Bioinformatics. 2010 Jun 15;26(12):i246-54. doi: 10.1093/bioinformatics/btq176.

7.

A semi-supervised method for drug-target interaction prediction with consistency in networks.

Chen H, Zhang Z.

PLoS One. 2013 May 7;8(5):e62975. doi: 10.1371/journal.pone.0062975. Print 2013.

8.

Computational probing protein-protein interactions targeting small molecules.

Wang YC, Chen SL, Deng NY, Wang Y.

Bioinformatics. 2016 Jan 15;32(2):226-34. doi: 10.1093/bioinformatics/btv528. Epub 2015 Sep 28.

PMID:
26415726
9.

Predicting drug-target interactions using restricted Boltzmann machines.

Wang Y, Zeng J.

Bioinformatics. 2013 Jul 1;29(13):i126-34. doi: 10.1093/bioinformatics/btt234.

10.

Prediction of drug-target interaction networks from the integration of chemical and genomic spaces.

Yamanishi Y, Araki M, Gutteridge A, Honda W, Kanehisa M.

Bioinformatics. 2008 Jul 1;24(13):i232-40. doi: 10.1093/bioinformatics/btn162.

11.
12.

Drug-target interaction prediction by random walk on the heterogeneous network.

Chen X, Liu MX, Yan GY.

Mol Biosyst. 2012 Jul 6;8(7):1970-8. doi: 10.1039/c2mb00002d. Epub 2012 Apr 26.

PMID:
22538619
13.

Kernel-based data fusion improves the drug-protein interaction prediction.

Wang YC, Zhang CH, Deng NY, Wang Y.

Comput Biol Chem. 2011 Dec 14;35(6):353-62. doi: 10.1016/j.compbiolchem.2011.10.003. Epub 2011 Oct 12.

PMID:
22099632
14.

Predicting drug-target interaction for new drugs using enhanced similarity measures and super-target clustering.

Shi JY, Yiu SM, Li Y, Leung HC, Chin FY.

Methods. 2015 Jul 15;83:98-104. doi: 10.1016/j.ymeth.2015.04.036. Epub 2015 May 6.

PMID:
25957673
15.

SELF-BLM: Prediction of drug-target interactions via self-training SVM.

Keum J, Nam H.

PLoS One. 2017 Feb 13;12(2):e0171839. doi: 10.1371/journal.pone.0171839. eCollection 2017.

16.

Large-scale prediction of drug-target interactions using protein sequences and drug topological structures.

Cao DS, Liu S, Xu QS, Lu HM, Huang JH, Hu QN, Liang YZ.

Anal Chim Acta. 2012 Nov 8;752:1-10. doi: 10.1016/j.aca.2012.09.021. Epub 2012 Sep 24.

PMID:
23101647
17.

Drug target prediction using adverse event report systems: a pharmacogenomic approach.

Takarabe M, Kotera M, Nishimura Y, Goto S, Yamanishi Y.

Bioinformatics. 2012 Sep 15;28(18):i611-i618. doi: 10.1093/bioinformatics/bts413.

18.

Preclinical pharmacokinetics: an approach towards safer and efficacious drugs.

Singh SS.

Curr Drug Metab. 2006 Feb;7(2):165-82. Review.

PMID:
16472106
19.

Improving compound-protein interaction prediction by building up highly credible negative samples.

Liu H, Sun J, Guan J, Zheng J, Zhou S.

Bioinformatics. 2015 Jun 15;31(12):i221-9. doi: 10.1093/bioinformatics/btv256.

20.

Protein-chemical interaction prediction via kernelized sparse learning SVM.

Shi Y, Zhang X, Liao X, Lin G, Schuurmans D.

Pac Symp Biocomput. 2013:41-52.

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