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10.1016/j.csbj.2016.04.004 http://scihub22266oqcxt.onion/10.1016/j.csbj.2016.04.004 C4887558!4887558!27293534     free     free     free Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Comput+Struct+Biotechnol+J 2016 ; 14 (ä): 177-84 Nephropedia Template TP {{tp|p=27293534|t=2016. Computational approaches in target identification and drug discovery |pdf=|usr=}}{{27293534}} gab.com Text Computational approaches in target identification and drug discovery JO: Comput Struct Biotechnol J http://www.kidney.de/pget.php?&tw=1&pmid=27293534 #FOAvip In the big data era, voluminous datasets are routinely acquired, stored and analyzed with the aim to inform biomedical discoveries and validate hypotheses. No doubt, data volume and diversity have dramatically increased by the advent of new technologies and open data initiatives. Big data are used across the whole drug discovery pipeline from target identification and mechanism of action to identification of novel leads and drug candidates. Such methods are depicted and discussed, with the aim to provide a general view of computational tools and databases available. We feel that big data leveraging needs to be cost-effective and focus on personalized medicine. For this, we propose the interplay of information technologies and (chemo)informatic tools on the basis of their synergy. Twit Text FOAVip Computational approaches in target identification and drug discovery ????Comput Struct Biotechnol J http://www.kidney.de/pget.php?&tw=1&pmid=27293534 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=27293534 #FOAvip English Wikipedia <ref>{{Cite pmid|27293534}}</ref> Computational approaches in target identification and drug discovery #MMPMID27293534 Katsila T; Spyroulias GA; Patrinos GP; Matsoukas MT Comput Struct Biotechnol J 2016[]; 14 (ä): 177-84 PMID27293534show ga In the big data era, voluminous datasets are routinely acquired, stored and analyzed with the aim to inform biomedical discoveries and validate hypotheses. No doubt, data volume and diversity have dramatically increased by the advent of new technologies and open data initiatives. Big data are used across the whole drug discovery pipeline from target identification and mechanism of action to identification of novel leads and drug candidates. Such methods are depicted and discussed, with the aim to provide a general view of computational tools and databases available. We feel that big data leveraging needs to be cost-effective and focus on personalized medicine. For this, we propose the interplay of information technologies and (chemo)informatic tools on the basis of their synergy. äComputational approaches in target identification and drug discovery (epmc).pdf DeepDyve Pubget Overpricing