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10.1016/j.compbiomed.2020.104180 http://scihub22266oqcxt.onion/10.1016/j.compbiomed.2020.104180 33360272!ä!33360272 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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\33360272.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Comput+Biol+Med 2021 ; 130 (ä): 104180 Nephropedia Template TP {{tp|p=33360272|t=2021. A semi-automatic methodology for analysing distributed and private biobanks |pdf=|usr=}}{{33360272}} gab.com Text A semi-automatic methodology for analysing distributed and private biobanks JO: Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=33360272 #FOAvip Privacy issues limit the analysis and cross-exploration of most distributed and private biobanks, often raised by the multiple dimensionality and sensitivity of the data associated with access restrictions and policies. These characteristics prevent collaboration between entities, constituting a barrier to emergent personalized and public health challenges, namely the discovery of new druggable targets, identification of disease-causing genetic variants, or the study of rare diseases. In this paper, we propose a semi-automatic methodology for the analysis of distributed and private biobanks. The strategies involved in the proposed methodology efficiently enable the creation and execution of unified genomic studies using distributed repositories, without compromising the information present in the datasets. We apply the methodology to a case study in the current Covid-19, ensuring the combination of the diagnostics from multiple entities while maintaining privacy through a completely identical procedure. Moreover, we show that the methodology follows a simple, intuitive, and practical scheme. Twit Text FOAVip A semi-automatic methodology for analysing distributed and private biobanks ????Comput Biol Med http://www.kidney.de/pget.php?&tw=1&pmid=33360272 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33360272 #FOAvip English Wikipedia <ref>{{Cite pmid|33360272}}</ref> A semi-automatic methodology for analysing distributed and private biobanks #MMPMID33360272 Almeida JR; Pratas D; Oliveira JL Comput Biol Med 2021[Mar]; 130 (ä): 104180 PMID33360272show ga Privacy issues limit the analysis and cross-exploration of most distributed and private biobanks, often raised by the multiple dimensionality and sensitivity of the data associated with access restrictions and policies. These characteristics prevent collaboration between entities, constituting a barrier to emergent personalized and public health challenges, namely the discovery of new druggable targets, identification of disease-causing genetic variants, or the study of rare diseases. In this paper, we propose a semi-automatic methodology for the analysis of distributed and private biobanks. The strategies involved in the proposed methodology efficiently enable the creation and execution of unified genomic studies using distributed repositories, without compromising the information present in the datasets. We apply the methodology to a case study in the current Covid-19, ensuring the combination of the diagnostics from multiple entities while maintaining privacy through a completely identical procedure. Moreover, we show that the methodology follows a simple, intuitive, and practical scheme. |*Biological Specimen Banks[MESH] |*COVID-19[MESH] |*Public Health[MESH] |*SARS-CoV-2[MESH]A semi-automatic methodology for analysing distributed and private bio(epmc).pdf DeepDyve Pubget Overpricing