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10.1177/1177625017696075 http://scihub22266oqcxt.onion/10.1177/1177625017696075 C5398297!5398297!28469412     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 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 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 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 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Gene+Regul+Syst+Bio 2017 ; 11 (ä): ä Nephropedia Template TP {{tp|p=28469412|t=2017. Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions |pdf=|usr=}}{{28469412}} gab.com Text Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions JO: Gene Regul Syst Bio http://www.kidney.de/pget.php?&tw=1&pmid=28469412 #FOAvip Drug-induced toxicity is a major public health concern that leads to patient morbidity and mortality. To address this problem, the Food and Drug Administration is working on the PredicTox initiative, a pilot research program on tyrosine kinase inhibitors, to build mechanistic and predictive models for drug-induced toxicity. This program involves integrating data acquired during preclinical studies and clinical trials within pharmaceutical company development programs that they have agreed to put in the public domain and in publicly available biological, pharmacological, and chemical databases. The integration process is accommodated by biomedical ontologies, a set of standardized vocabularies that define terms and logical relationships between them in each vocabulary. We describe a few programs that have used ontologies to address biomedical questions. The PredicTox effort is leveraging the experience gathered from these early initiatives to develop an infrastructure that allows evaluation of the hypothesis that having a mechanistic understanding underlying adverse drug reactions will improve the capacity to understand drug-induced clinical adverse drug reactions. Twit Text FOAVip Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions ????Gene Regul Syst Bio http://www.kidney.de/pget.php?&tw=1&pmid=28469412 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28469412 #FOAvip English Wikipedia <ref>{{Cite pmid|28469412}}</ref> Use of Biomedical Ontologies for Integration of Biological Knowledge for Learning and Prediction of Adverse Drug Reactions #MMPMID28469412 Zaman S; Sarntivijai S; Abernethy DR Gene Regul Syst Bio 2017[]; 11 (ä): ä PMID28469412show ga Drug-induced toxicity is a major public health concern that leads to patient morbidity and mortality. To address this problem, the Food and Drug Administration is working on the PredicTox initiative, a pilot research program on tyrosine kinase inhibitors, to build mechanistic and predictive models for drug-induced toxicity. This program involves integrating data acquired during preclinical studies and clinical trials within pharmaceutical company development programs that they have agreed to put in the public domain and in publicly available biological, pharmacological, and chemical databases. The integration process is accommodated by biomedical ontologies, a set of standardized vocabularies that define terms and logical relationships between them in each vocabulary. We describe a few programs that have used ontologies to address biomedical questions. The PredicTox effort is leveraging the experience gathered from these early initiatives to develop an infrastructure that allows evaluation of the hypothesis that having a mechanistic understanding underlying adverse drug reactions will improve the capacity to understand drug-induced clinical adverse drug reactions. äUse of Biomedical Ontologies for Integration of Biological Knowledge f(epmc).pdf DeepDyve Pubget Overpricing