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Items: 1 to 20 of 253

1.

Computational drug repositioning through heterogeneous network clustering.

Wu C, Gudivada RC, Aronow BJ, Jegga AG.

BMC Syst Biol. 2013;7 Suppl 5:S6. doi: 10.1186/1752-0509-7-S5-S6. Epub 2013 Dec 9.

2.

A two-tiered unsupervised clustering approach for drug repositioning through heterogeneous data integration.

Hameed PN, Verspoor K, Kusljic S, Halgamuge S.

BMC Bioinformatics. 2018 Apr 11;19(1):129. doi: 10.1186/s12859-018-2123-4.

3.

DrugNet: network-based drug-disease prioritization by integrating heterogeneous data.

Martínez V, Navarro C, Cano C, Fajardo W, Blanco A.

Artif Intell Med. 2015 Jan;63(1):41-9. doi: 10.1016/j.artmed.2014.11.003. Epub 2015 Jan 13.

PMID:
25704113
4.

Using a novel computational drug-repositioning approach (DrugPredict) to rapidly identify potent drug candidates for cancer treatment.

Nagaraj AB, Wang QQ, Joseph P, Zheng C, Chen Y, Kovalenko O, Singh S, Armstrong A, Resnick K, Zanotti K, Waggoner S, Xu R, DiFeo A.

Oncogene. 2018 Jan 18;37(3):403-414. doi: 10.1038/onc.2017.328. Epub 2017 Oct 2.

5.

Prediction of Novel Drugs for Hepatocellular Carcinoma Based on Multi-Source Random Walk.

Yu L, Su R, Wang B, Zhang L, Zou Y, Zhang J, Gao L.

IEEE/ACM Trans Comput Biol Bioinform. 2017 Jul-Aug;14(4):966-977. doi: 10.1109/TCBB.2016.2550453. Epub 2016 Apr 5.

PMID:
27076463
6.

Drug repositioning by integrating target information through a heterogeneous network model.

Wang W, Yang S, Zhang X, Li J.

Bioinformatics. 2014 Oct 15;30(20):2923-30. doi: 10.1093/bioinformatics/btu403. Epub 2014 Jun 27.

7.

Drug target prediction and repositioning using an integrated network-based approach.

Emig D, Ivliev A, Pustovalova O, Lancashire L, Bureeva S, Nikolsky Y, Bessarabova M.

PLoS One. 2013 Apr 4;8(4):e60618. doi: 10.1371/journal.pone.0060618. Print 2013.

8.

Inferring new indications for approved drugs via random walk on drug-disease heterogenous networks.

Liu H, Song Y, Guan J, Luo L, Zhuang Z.

BMC Bioinformatics. 2016 Dec 23;17(Suppl 17):539. doi: 10.1186/s12859-016-1336-7.

9.

Network-based drug ranking and repositioning with respect to DrugBank therapeutic categories.

Re M, Valentini G.

IEEE/ACM Trans Comput Biol Bioinform. 2013 Nov-Dec;10(6):1359-71. doi: 10.1109/TCBB.2013.62.

10.

Transcriptomic-Guided Drug Repositioning Supported by a New Bioinformatics Search Tool: geneXpharma.

Turanli B, Gulfidan G, Arga KY.

OMICS. 2017 Oct;21(10):584-591. doi: 10.1089/omi.2017.0127.

PMID:
29049014
11.

Computational Drug Repositioning: A Lateral Approach to Traditional Drug Discovery?

Sahu NU, Kharkar PS.

Curr Top Med Chem. 2016;16(19):2069-77. Review.

PMID:
26881717
12.

Prediction of new drug indications based on clinical data and network modularity.

Yu L, Ma X, Zhang L, Zhang J, Gao L.

Sci Rep. 2016 Sep 28;6:32530. doi: 10.1038/srep32530.

13.

DMAP: a connectivity map database to enable identification of novel drug repositioning candidates.

Huang H, Nguyen T, Ibrahim S, Shantharam S, Yue Z, Chen JY.

BMC Bioinformatics. 2015;16 Suppl 13:S4. doi: 10.1186/1471-2105-16-S13-S4. Epub 2015 Sep 25.

14.

Drug repositioning in SLE: crowd-sourcing, literature-mining and Big Data analysis.

Grammer AC, Ryals MM, Heuer SE, Robl RD, Madamanchi S, Davis LS, Lauwerys B, Catalina MD, Lipsky PE.

Lupus. 2016 Sep;25(10):1150-70. doi: 10.1177/0961203316657437. Review.

PMID:
27497259
15.

MeSHDD: Literature-based drug-drug similarity for drug repositioning.

Brown AS, Patel CJ.

J Am Med Inform Assoc. 2017 May 1;24(3):614-618. doi: 10.1093/jamia/ocw142.

16.

MD-Miner: a network-based approach for personalized drug repositioning.

Wu H, Miller E, Wijegunawardana D, Regan K, Payne PRO, Li F.

BMC Syst Biol. 2017 Oct 3;11(Suppl 5):86. doi: 10.1186/s12918-017-0462-9.

17.

DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing.

Issa NT, Kruger J, Wathieu H, Raja R, Byers SW, Dakshanamurthy S.

BMC Bioinformatics. 2016 May 5;17(1):202. doi: 10.1186/s12859-016-1065-y.

18.

Systematic integration of biomedical knowledge prioritizes drugs for repurposing.

Himmelstein DS, Lizee A, Hessler C, Brueggeman L, Chen SL, Hadley D, Green A, Khankhanian P, Baranzini SE.

Elife. 2017 Sep 22;6. pii: e26726. doi: 10.7554/eLife.26726.

19.

PhenoPredict: A disease phenome-wide drug repositioning approach towards schizophrenia drug discovery.

Xu R, Wang Q.

J Biomed Inform. 2015 Aug;56:348-55. doi: 10.1016/j.jbi.2015.06.027. Epub 2015 Jul 4.

20.

Drug repurposing by integrated literature mining and drug-gene-disease triangulation.

Sun P, Guo J, Winnenburg R, Baumbach J.

Drug Discov Today. 2017 Apr;22(4):615-619. doi: 10.1016/j.drudis.2016.10.008. Epub 2016 Oct 22.

PMID:
27780789

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