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10.3402/jev.v4.27497 http://scihub22266oqcxt.onion/10.3402/jev.v4.27497 C4553261!4553261!26320941     free     free     free Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 233.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       J+Extracell+Vesicles 2015 ; 4 (ä): ä Nephropedia Template TP {{tp|p=26320941|t=2015. Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies |pdf=|usr=}}{{26320941}} gab.com Text Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies JO: J Extracell Vesicles http://www.kidney.de/pget.php?&tw=1&pmid=26320941 #FOAvip The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data. Twit Text FOAVip Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies ????J Extracell Vesicles http://www.kidney.de/pget.php?&tw=1&pmid=26320941 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26320941 #FOAvip English Wikipedia <ref>{{Cite pmid|26320941}}</ref> Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies #MMPMID26320941 Subramanian SL; Kitchen RR; Alexander R; Carter BS; Cheung KH; Laurent LC; Pico A; Roberts LR; Roth ME; Rozowsky JS; Su AI; Gerstein MB; Milosavljevic A J Extracell Vesicles 2015[]; 4 (ä): ä PMID26320941show ga The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data. äIntegration of extracellular RNA profiling data using metadata, biomed(epmc).pdf DeepDyve Pubget Overpricing