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10.1016/j.tube.2015.05.012 http://scihub22266oqcxt.onion/10.1016/j.tube.2015.05.012 C4554888!4554888!26190839     free     free     free       Tuberculosis+(Edinb) 2015 ; 95 (5): 570-4 Nephropedia Template TP {{tp|p=26190839|t=2015. A Tuberculosis Ontology for Host Systems Biology |pdf=|usr=}}{{26190839}} gab.com Text A Tuberculosis Ontology for Host Systems Biology JO: Tuberculosis (Edinb) http://www.kidney.de/pget.php?&tw=1&pmid=26190839 #FOAvip A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a means to readily compare samples from different research groups, a significant quantity of potentially informative data is largely ignored by researchers. To facilitate standardizing data across studies, a simple ontology of TB terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address animal models and experimental systems, and existing clinically focused terminology was modified and adapted. This ontology can be used to annotate host TB data in public databases and collaborations, thereby standardizing database searches and allowing researchers to more easily compare results. To demonstrate the utility of a standard TB ontology for host systems biology, a web application was developed to annotate and compare human and animal model gene expression data sets. Twit Text FOAVip A Tuberculosis Ontology for Host Systems Biology ????Tuberculosis (Edinb) http://www.kidney.de/pget.php?&tw=1&pmid=26190839 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26190839 #FOAvip English Wikipedia <ref>{{Cite pmid|26190839}}</ref> A Tuberculosis Ontology for Host Systems Biology #MMPMID26190839 Levine DM; Dutta NK; Eckels J; Scanga C; Stein C; Mehra S; Kaushal D; Karakousis PC; Salamon H Tuberculosis (Edinb) 2015[Sep]; 95 (5): 570-4 PMID26190839show ga A major hurdle facing tuberculosis (TB) investigators who want to utilize a rapidly growing body of data from both systems biology approaches and omics technologies is the lack of a standard vocabulary for data annotation and reporting. Lacking a means to readily compare samples from different research groups, a significant quantity of potentially informative data is largely ignored by researchers. To facilitate standardizing data across studies, a simple ontology of TB terms was developed to provide a common vocabulary for annotating data sets. New terminology was developed to address animal models and experimental systems, and existing clinically focused terminology was modified and adapted. This ontology can be used to annotate host TB data in public databases and collaborations, thereby standardizing database searches and allowing researchers to more easily compare results. To demonstrate the utility of a standard TB ontology for host systems biology, a web application was developed to annotate and compare human and animal model gene expression data sets. äA Tuberculosis Ontology for Host Systems Biology (epmc).pdf DeepDyve Pubget Overpricing