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10.1002/wsbm.1337 http://scihub22266oqcxt.onion/10.1002/wsbm.1337 C4845762!4845762!27080087     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Wiley+Interdiscip+Rev+Syst+Biol+Med 2016 ; 8 (3): 186-210 Nephropedia Template TP {{tp|p=27080087|t=2016. Computational Approaches to Drug Repurposing and Pharmacology |pdf=|usr=}}{{27080087}} gab.com Text Computational Approaches to Drug Repurposing and Pharmacology JO: Wiley Interdiscip Rev Syst Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=27080087 #FOAvip Data in the biological, chemical, and clinical domains are accumulating at ever-increasing rates and have the potential to accelerate and inform drug development in new ways. Challenges and opportunities now lie in developing analytic tools to transform these often complex and heterogeneous data into testable hypotheses and actionable insights. This is the aim of computational pharmacology, which uses in silico techniques to better understand and predict how drugs affect biological systems, which can in turn improve clinical use, avoid unwanted side effects, and guide selection and development of better treatments. One exciting application of computational pharmacology is drug repurposing- finding new uses for existing drugs. Already yielding many promising candidates, this strategy has the potential to improve the efficiency of the drug development process and reach patient populations with previously unmet needs such as those with rare diseases. While current techniques in computational pharmacology and drug repurposing often focus on just a single data modality such as gene expression or drug-target interactions, we rationalize that methods such as matrix factorization that can integrate data within and across diverse data types have the potential to improve predictive performance and provide a fuller picture of a drug's pharmacological action. Twit Text FOAVip Computational Approaches to Drug Repurposing and Pharmacology ????Wiley Interdiscip Rev Syst Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=27080087 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27080087 #FOAvip English Wikipedia <ref>{{Cite pmid|27080087}}</ref> Computational Approaches to Drug Repurposing and Pharmacology #MMPMID27080087 Hodos RA; Kidd BA; Khader S; Readhead BP; Dudley JT Wiley Interdiscip Rev Syst Biol Med 2016[May]; 8 (3): 186-210 PMID27080087show ga Data in the biological, chemical, and clinical domains are accumulating at ever-increasing rates and have the potential to accelerate and inform drug development in new ways. Challenges and opportunities now lie in developing analytic tools to transform these often complex and heterogeneous data into testable hypotheses and actionable insights. This is the aim of computational pharmacology, which uses in silico techniques to better understand and predict how drugs affect biological systems, which can in turn improve clinical use, avoid unwanted side effects, and guide selection and development of better treatments. One exciting application of computational pharmacology is drug repurposing- finding new uses for existing drugs. Already yielding many promising candidates, this strategy has the potential to improve the efficiency of the drug development process and reach patient populations with previously unmet needs such as those with rare diseases. While current techniques in computational pharmacology and drug repurposing often focus on just a single data modality such as gene expression or drug-target interactions, we rationalize that methods such as matrix factorization that can integrate data within and across diverse data types have the potential to improve predictive performance and provide a fuller picture of a drug's pharmacological action. äComputational Approaches to Drug Repurposing and Pharmacology (epmc).pdf DeepDyve Pubget Overpricing