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Items: 1 to 20 of 147

1.

DrugComboRanker: drug combination discovery based on target network analysis.

Huang L, Li F, Sheng J, Xia X, Ma J, Zhan M, Wong ST.

Bioinformatics. 2014 Jun 15;30(12):i228-36. doi: 10.1093/bioinformatics/btu278.

2.

Diffusion mapping of drug targets on disease signaling network elements reveals drug combination strategies.

Xu J, Regan-Fendt K, Deng S, Carson WE, Payne PRO, Li F.

Pac Symp Biocomput. 2018;23:92-103.

3.

Biomolecular Network-Based Synergistic Drug Combination Discovery.

Li X, Qin G, Yang Q, Chen L, Xie L.

Biomed Res Int. 2016;2016:8518945. Epub 2016 Nov 7. Review.

4.

CDA: combinatorial drug discovery using transcriptional response modules.

Lee JH, Kim DG, Bae TJ, Rho K, Kim JT, Lee JJ, Jang Y, Kim BC, Park KM, Kim S.

PLoS One. 2012;7(8):e42573. doi: 10.1371/journal.pone.0042573. Epub 2012 Aug 8.

5.

TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples.

He L, Wennerberg K, Aittokallio T, Tang J.

Bioinformatics. 2015 Jun 1;31(11):1866-8. doi: 10.1093/bioinformatics/btv067. Epub 2015 Jan 31.

6.

Drosophila as a novel therapeutic discovery tool for thyroid cancer.

Das T, Cagan R.

Thyroid. 2010 Jul;20(7):689-95. doi: 10.1089/thy.2010.1637. Review.

PMID:
20578898
7.

Systematic identification of feature combinations for predicting drug response with Bayesian multi-view multi-task linear regression.

Ammad-Ud-Din M, Khan SA, Wennerberg K, Aittokallio T.

Bioinformatics. 2017 Jul 15;33(14):i359-i368. doi: 10.1093/bioinformatics/btx266.

8.

Proof of concept: network and systems biology approaches aid in the discovery of potent anticancer drug combinations.

Azmi AS, Wang Z, Philip PA, Mohammad RM, Sarkar FH.

Mol Cancer Ther. 2010 Dec;9(12):3137-44. doi: 10.1158/1535-7163.MCT-10-0642. Epub 2010 Nov 1. Review.

9.

Target inhibition networks: predicting selective combinations of druggable targets to block cancer survival pathways.

Tang J, Karhinen L, Xu T, Szwajda A, Yadav B, Wennerberg K, Aittokallio T.

PLoS Comput Biol. 2013;9(9):e1003226. doi: 10.1371/journal.pcbi.1003226. Epub 2013 Sep 12.

10.

Synergistic interactions between camptothecin and EGFR or RAC1 inhibitors and between imatinib and Notch signaling or RAC1 inhibitors in glioblastoma cell lines.

Sooman L, Ekman S, Andersson C, Kultima HG, Isaksson A, Johansson F, Bergqvist M, Blomquist E, Lennartsson J, Gullbo J.

Cancer Chemother Pharmacol. 2013 Aug;72(2):329-40. doi: 10.1007/s00280-013-2197-7. Epub 2013 Jun 5.

PMID:
23736154
11.

Systems biology approaches for advancing the discovery of effective drug combinations.

Ryall KA, Tan AC.

J Cheminform. 2015 Feb 26;7:7. doi: 10.1186/s13321-015-0055-9. eCollection 2015.

12.

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
13.

Distinctive Behaviors of Druggable Proteins in Cellular Networks.

Mitsopoulos C, Schierz AC, Workman P, Al-Lazikani B.

PLoS Comput Biol. 2015 Dec 23;11(12):e1004597. doi: 10.1371/journal.pcbi.1004597. eCollection 2015 Dec.

14.

[Development of antituberculous drugs: current status and future prospects].

Tomioka H, Namba K.

Kekkaku. 2006 Dec;81(12):753-74. Review. Japanese.

PMID:
17240921
15.

Drug response prediction by inferring pathway-response associations with kernelized Bayesian matrix factorization.

Ammad-Ud-Din M, Khan SA, Malani D, Murumägi A, Kallioniemi O, Aittokallio T, Kaski S.

Bioinformatics. 2016 Sep 1;32(17):i455-i463. doi: 10.1093/bioinformatics/btw433.

PMID:
27587662
16.

DT-Web: a web-based application for drug-target interaction and drug combination prediction through domain-tuned network-based inference.

Alaimo S, Bonnici V, Cancemi D, Ferro A, Giugno R, Pulvirenti A.

BMC Syst Biol. 2015;9 Suppl 3:S4. doi: 10.1186/1752-0509-9-S3-S4. Epub 2015 Jun 1.

17.

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.

18.

Phenome-driven disease genetics prediction toward drug discovery.

Chen Y, Li L, Zhang GQ, Xu R.

Bioinformatics. 2015 Jun 15;31(12):i276-83. doi: 10.1093/bioinformatics/btv245.

19.

An Integrated Data Driven Approach to Drug Repositioning Using Gene-Disease Associations.

Mullen J, Cockell SJ, Woollard P, Wipat A.

PLoS One. 2016 May 19;11(5):e0155811. doi: 10.1371/journal.pone.0155811. eCollection 2016.

20.

DTome: a web-based tool for drug-target interactome construction.

Sun J, Wu Y, Xu H, Zhao Z.

BMC Bioinformatics. 2012 Jun 11;13 Suppl 9:S7. doi: 10.1186/1471-2105-13-S9-S7.

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