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Results: 1 to 20 of 25

Cited In for PubMed (Select 20838579)

1.

Systematic evaluation of connectivity map for disease indications.

Cheng J, Yang L, Kumar V, Agarwal P.

Genome Med. 2014 Dec 2;6(12):540. doi: 10.1186/s13073-014-0095-1. eCollection 2014.

2.

Identification of structural features in chemicals associated with cancer drug response: a systematic data-driven analysis.

Khan SA, Virtanen S, Kallioniemi OP, Wennerberg K, Poso A, Kaski S.

Bioinformatics. 2014 Sep 1;30(17):i497-504. doi: 10.1093/bioinformatics/btu456.

3.

Towards structural systems pharmacology to study complex diseases and personalized medicine.

Xie L, Ge X, Tan H, Xie L, Zhang Y, Hart T, Yang X, Bourne PE.

PLoS Comput Biol. 2014 May 15;10(5):e1003554. doi: 10.1371/journal.pcbi.1003554. eCollection 2014 May.

4.

Probabilistic drug connectivity mapping.

Parkkinen JA, Kaski S.

BMC Bioinformatics. 2014 Apr 17;15:113. doi: 10.1186/1471-2105-15-113.

5.

Network based elucidation of drug response: from modulators to targets.

Iorio F, Saez-Rodriguez J, di Bernardo D.

BMC Syst Biol. 2013 Dec 13;7:139. doi: 10.1186/1752-0509-7-139. Review.

6.

STITCH 4: integration of protein-chemical interactions with user data.

Kuhn M, Szklarczyk D, Pletscher-Frankild S, Blicher TH, von Mering C, Jensen LJ, Bork P.

Nucleic Acids Res. 2014 Jan;42(Database issue):D401-7. doi: 10.1093/nar/gkt1207. Epub 2013 Nov 28.

7.

Prediction of drug-target interactions for drug repositioning only based on genomic expression similarity.

Wang K, Sun J, Zhou S, Wan C, Qin S, Li C, He L, Yang L.

PLoS Comput Biol. 2013;9(11):e1003315. doi: 10.1371/journal.pcbi.1003315. Epub 2013 Nov 7. Erratum in: PLoS Comput Biol. 2013 Nov;9(11). doi:10.1371/annotation/958d4c23-4f1e-4579-b6ef-8ae1f828b1dd.

8.

CellFateScout - a bioinformatics tool for elucidating small molecule signaling pathways that drive cells in a specific direction.

Siatkowski M, Liebscher V, Fuellen G.

Cell Commun Signal. 2013 Nov 8;11:85. doi: 10.1186/1478-811X-11-85.

9.

Integrated analysis of drug-induced gene expression profiles predicts novel hERG inhibitors.

Babcock JJ, Du F, Xu K, Wheelan SJ, Li M.

PLoS One. 2013 Jul 23;8(7):e69513. doi: 10.1371/journal.pone.0069513. Print 2013.

10.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data.

McArt DG, Dunne PD, Blayney JK, Salto-Tellez M, Van Schaeybroeck S, Hamilton PW, Zhang SD.

PLoS One. 2013 Jun 26;8(6):e66902. Print 2013.

11.

Drug repositioning: a machine-learning approach through data integration.

Napolitano F, Zhao Y, Moreira VM, Tagliaferri R, Kere J, D'Amato M, Greco D.

J Cheminform. 2013 Jun 22;5(1):30. doi: 10.1186/1758-2946-5-30.

12.

Characterization of drug-induced transcriptional modules: towards drug repositioning and functional understanding.

Iskar M, Zeller G, Blattmann P, Campillos M, Kuhn M, Kaminska KH, Runz H, Gavin AC, Pepperkok R, van Noort V, Bork P.

Mol Syst Biol. 2013;9:662. doi: 10.1038/msb.2013.20.

13.

Role of the K(Ca)3.1 K+ channel in auricular lymph node CD4+ T-lymphocyte function of the delayed-type hypersensitivity model.

Ohya S, Nakamura E, Horiba S, Kito H, Matsui M, Yamamura H, Imaizumi Y.

Br J Pharmacol. 2013 Jul;169(5):1011-23. doi: 10.1111/bph.12215.

14.

Transcriptional responses of in vivo praziquantel exposure in schistosomes identifies a functional role for calcium signalling pathway member CamKII.

You H, McManus DP, Hu W, Smout MJ, Brindley PJ, Gobert GN.

PLoS Pathog. 2013 Mar;9(3):e1003254. doi: 10.1371/journal.ppat.1003254. Epub 2013 Mar 28.

15.

FacPad: Bayesian sparse factor modeling for the inference of pathways responsive to drug treatment.

Ma H, Zhao H.

Bioinformatics. 2012 Oct 15;28(20):2662-70. doi: 10.1093/bioinformatics/bts502. Epub 2012 Aug 24.

16.

Transcriptional data: a new gateway to drug repositioning?

Iorio F, Rittman T, Ge H, Menden M, Saez-Rodriguez J.

Drug Discov Today. 2013 Apr;18(7-8):350-7. doi: 10.1016/j.drudis.2012.07.014. Epub 2012 Aug 7.

17.

Comprehensive data-driven analysis of the impact of chemoinformatic structure on the genome-wide biological response profiles of cancer cells to 1159 drugs.

Khan SA, Faisal A, Mpindi JP, Parkkinen JA, Kalliokoski T, Poso A, Kallioniemi OP, Wennerberg K, Kaski S.

BMC Bioinformatics. 2012 May 30;13:112. doi: 10.1186/1471-2105-13-112.

18.

Determination of minimal transcriptional signatures of compounds for target prediction.

Nigsch F, Hutz J, Cornett B, Selinger DW, McAllister G, Bandyopadhyay S, Loureiro J, Jenkins JL.

EURASIP J Bioinform Syst Biol. 2012 May 10;2012(1):2. doi: 10.1186/1687-4153-2012-2.

19.

Large-scale elucidation of drug response pathways in humans.

Silberberg Y, Gottlieb A, Kupiec M, Ruppin E, Sharan R.

J Comput Biol. 2012 Feb;19(2):163-74. doi: 10.1089/cmb.2011.0264.

20.

Systems pharmacology: network analysis to identify multiscale mechanisms of drug action.

Zhao S, Iyengar R.

Annu Rev Pharmacol Toxicol. 2012;52:505-21. doi: 10.1146/annurev-pharmtox-010611-134520. Review.

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