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Items: 1 to 20 of 26

1.

In silico prediction of drug-target interaction networks based on drug chemical structure and protein sequences.

Li Z, Han P, You ZH, Li X, Zhang Y, Yu H, Nie R, Chen X.

Sci Rep. 2017 Sep 11;7(1):11174. doi: 10.1038/s41598-017-10724-0.

2.

Large-scale identification of adverse drug reaction-related proteins through a random walk model.

Chen X, Shi H, Yang F, Yang L, Lv Y, Wang S, Dai E, Sun D, Jiang W.

Sci Rep. 2016 Nov 2;6:36325. doi: 10.1038/srep36325.

3.

Illuminating drug action by network integration of disease genes: a case study of myocardial infarction.

Wang RS, Loscalzo J.

Mol Biosyst. 2016 Apr 26;12(5):1653-66. doi: 10.1039/c6mb00052e.

4.

An Integrative Pharmacogenomic Approach Identifies Two-drug Combination Therapies for Personalized Cancer Medicine.

Liu Y, Fei T, Zheng X, Brown M, Zhang P, Liu XS, Wang H.

Sci Rep. 2016 Feb 26;6:22120. doi: 10.1038/srep22120.

5.

2D and 3D similarity landscape analysis identifies PARP as a novel off-target for the drug Vatalanib.

Gohlke BO, Overkamp T, Richter A, Richter A, Daniel PT, Gillissen B, Preissner R.

BMC Bioinformatics. 2015 Sep 24;16:308. doi: 10.1186/s12859-015-0730-x.

6.

PhIN: A Protein Pharmacology Interaction Network Database.

Wang Z, Li J, Dang R, Liang L, Lin J.

CPT Pharmacometrics Syst Pharmacol. 2015 Mar;4(3):e00025. doi: 10.1002/psp4.25. Epub 2015 Mar 18.

7.

A survey on the computational approaches to identify drug targets in the postgenomic era.

Dai YF, Zhao XM.

Biomed Res Int. 2015;2015:239654. doi: 10.1155/2015/239654. Epub 2015 Apr 28. Review.

8.

The Use of Chemical-Chemical Interaction and Chemical Structure to Identify New Candidate Chemicals Related to Lung Cancer.

Chen L, Yang J, Zheng M, Kong X, Huang T, Cai YD.

PLoS One. 2015 Jun 5;10(6):e0128696. doi: 10.1371/journal.pone.0128696. eCollection 2015.

9.

Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

Perez-Lopez ÁR, Szalay KZ, Türei D, Módos D, Lenti K, Korcsmáros T, Csermely P.

Sci Rep. 2015 May 11;5:10182. doi: 10.1038/srep10182.

10.

Discovery of new candidate genes related to brain development using protein interaction information.

Chen L, Chu C, Kong X, Huang T, Cai YD.

PLoS One. 2015 Jan 30;10(1):e0118003. doi: 10.1371/journal.pone.0118003. eCollection 2015.

11.

Molecularly and clinically related drugs and diseases are enriched in phenotypically similar drug-disease pairs.

Vogt I, Prinz J, Campillos M.

Genome Med. 2014 Aug 17;6(7):52. doi: 10.1186/s13073-014-0052-z. eCollection 2014.

12.

A systematic investigation of computation models for predicting Adverse Drug Reactions (ADRs).

Kuang Q, Wang M, Li R, Dong Y, Li Y, Li M.

PLoS One. 2014 Sep 2;9(9):e105889. doi: 10.1371/journal.pone.0105889. eCollection 2014.

13.

Suberoylanilide hydroxamic acid (SAHA)-induced dynamics of a human histone deacetylase protein interaction network.

Sardiu ME, Smith KT, Groppe BD, Gilmore JM, Saraf A, Egidy R, Peak A, Seidel CW, Florens L, Workman JL, Washburn MP.

Mol Cell Proteomics. 2014 Nov;13(11):3114-25. doi: 10.1074/mcp.M113.037127. Epub 2014 Jul 29.

14.

SuperPred: update on drug classification and target prediction.

Nickel J, Gohlke BO, Erehman J, Banerjee P, Rong WW, Goede A, Dunkel M, Preissner R.

Nucleic Acids Res. 2014 Jul;42(Web Server issue):W26-31. doi: 10.1093/nar/gku477. Epub 2014 May 30.

15.

Node interference and robustness: performing virtual knock-out experiments on biological networks: the case of leukocyte integrin activation network.

Scardoni G, Montresor A, Tosadori G, Laudanna C.

PLoS One. 2014 Feb 20;9(2):e88938. doi: 10.1371/journal.pone.0088938. eCollection 2014.

16.

Delivery of small molecules for bone regenerative engineering: preclinical studies and potential clinical applications.

Laurencin CT, Ashe KM, Henry N, Kan HM, Lo KW.

Drug Discov Today. 2014 Jun;19(6):794-800. doi: 10.1016/j.drudis.2014.01.012. Epub 2014 Feb 6. Review.

17.

One-day treatment of small molecule 8-bromo-cyclic AMP analogue induces cell-based VEGF production for in vitro angiogenesis and osteoblastic differentiation.

Lo KW, Kan HM, Gagnon KA, Laurencin CT.

J Tissue Eng Regen Med. 2016 Oct;10(10):867-875. doi: 10.1002/term.1839. Epub 2013 Nov 6.

18.

Small-molecule based musculoskeletal regenerative engineering.

Lo KW, Jiang T, Gagnon KA, Nelson C, Laurencin CT.

Trends Biotechnol. 2014 Feb;32(2):74-81. doi: 10.1016/j.tibtech.2013.12.002. Epub 2014 Jan 6. Review.

19.

Determining molecular predictors of adverse drug reactions with causality analysis based on structure learning.

Liu M, Cai R, Hu Y, Matheny ME, Sun J, Hu J, Xu H.

J Am Med Inform Assoc. 2014 Mar-Apr;21(2):245-51. doi: 10.1136/amiajnl-2013-002051. Epub 2013 Dec 11.

20.

Prediction of effective drug combinations by chemical interaction, protein interaction and target enrichment of KEGG pathways.

Chen L, Li BQ, Zheng MY, Zhang J, Feng KY, Cai YD.

Biomed Res Int. 2013;2013:723780. doi: 10.1155/2013/723780. Epub 2013 Sep 5.

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