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10.1186/s12859-016-1065-y

http://scihub22266oqcxt.onion/10.1186/s12859-016-1065-y
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suck abstract from ncbi


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pmid27151405      BMC+Bioinformatics 2016 ; 17 (ä): ä
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  • DrugGenEx-Net: a novel computational platform for systems pharmacology and gene expression-based drug repurposing #MMPMID27151405
  • Issa NT; Kruger J; Wathieu H; Raja R; Byers SW; Dakshanamurthy S
  • BMC Bioinformatics 2016[]; 17 (ä): ä PMID27151405show ga
  • Background: The targeting of disease-related proteins is important for drug discovery, and yet target-based discovery has not been fruitful. Contextualizing overall biological processes is critical to formulating successful drug-disease hypotheses. Network pharmacology helps to overcome target-based bottlenecks through systems biology analytics, such as protein-protein interaction (PPI) networks and pathway regulation. Results: We present a systems polypharmacology platform entitled DrugGenEx-Net (DGE-NET). DGE-NET predicts empirical drug-target (DT) interactions, integrates interaction pairs into a multi-tiered network analysis, and ultimately predicts disease-specific drug polypharmacology through systems-based gene expression analysis. Incorporation of established biological network annotations for protein target-disease, ?signaling pathway, ?molecular function, and protein-protein interactions enhances predicted DT effects on disease pathophysiology. Over 50 drug-disease and 100 drug-pathway predictions are validated. For example, the predicted systems pharmacology of the cholesterol-lowering agent ezetimibe corroborates its potential carcinogenicity.When disease-specific gene expression analysis is integrated, DGE-NET prioritizes known therapeutics/experimental drugs as well as their contra-indications. Proof-of-concept is established for immune-related rheumatoid arthritis and inflammatory bowel disease, as well as neuro-degenerative Alzheimer?s and Parkinson?s diseases. Conclusions: DGE-NET is a novel computational method that predicting drug therapeutic and counter-therapeutic indications by uniquely integrating systems pharmacology with gene expression analysis. DGE-NET correctly predicts various drug-disease indications by linking the biological activity of drugs and diseases at multiple tiers of biological action, and is therefore a useful approach to identifying drug candidates for re-purposing. Electronic supplementary material: The online version of this article (doi:10.1186/s12859-016-1065-y) contains supplementary material, which is available to authorized users.
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