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10.1111/tbed.13588 http://scihub22266oqcxt.onion/10.1111/tbed.13588 32306500!7264654!32306500     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 265.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Transbound+Emerg+Dis 2020 ; 67 (4): 1453-1462 Nephropedia Template TP {{tp|p=32306500|t=2020. Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak |pdf=|usr=}}{{32306500}} gab.com Text Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak JO: Transbound Emerg Dis http://www.kidney.de/pget.php?&tw=1&pmid=32306500 #FOAvip Pre-clinical responses to fast-moving infectious disease outbreaks heavily depend on choosing the best isolates for animal models that inform diagnostics, vaccines and treatments. Current approaches are driven by practical considerations (e.g. first available virus isolate) rather than a detailed analysis of the characteristics of the virus strain chosen, which can lead to animal models that are not representative of the circulating or emerging clusters. Here, we suggest a combination of epidemiological, experimental and bioinformatic considerations when choosing virus strains for animal model generation. We discuss the currently chosen SARS-CoV-2 strains for international coronavirus disease (COVID-19) models in the context of their phylogeny as well as in a novel alignment-free bioinformatic approach. Unlike phylogenetic trees, which focus on individual shared mutations, this new approach assesses genome-wide co-developing functionalities and hence offers a more fluid view of the 'cloud of variances' that RNA viruses are prone to accumulate. This joint approach concludes that while the current animal models cover the existing viral strains adequately, there is substantial evolutionary activity that is likely not considered by the current models. Based on insights from the non-discrete alignment-free approach and experimental observations, we suggest isolates for future animal models. Twit Text FOAVip Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak ????Transbound Emerg Dis http://www.kidney.de/pget.php?&tw=1&pmid=32306500 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32306500 #FOAvip English Wikipedia <ref>{{Cite pmid|32306500}}</ref> Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak #MMPMID32306500 Bauer DC; Tay AP; Wilson LOW; Reti D; Hosking C; McAuley AJ; Pharo E; Todd S; Stevens V; Neave MJ; Tachedjian M; Drew TW; Vasan SS Transbound Emerg Dis 2020[Jul]; 67 (4): 1453-1462 PMID32306500show ga Pre-clinical responses to fast-moving infectious disease outbreaks heavily depend on choosing the best isolates for animal models that inform diagnostics, vaccines and treatments. Current approaches are driven by practical considerations (e.g. first available virus isolate) rather than a detailed analysis of the characteristics of the virus strain chosen, which can lead to animal models that are not representative of the circulating or emerging clusters. Here, we suggest a combination of epidemiological, experimental and bioinformatic considerations when choosing virus strains for animal model generation. We discuss the currently chosen SARS-CoV-2 strains for international coronavirus disease (COVID-19) models in the context of their phylogeny as well as in a novel alignment-free bioinformatic approach. Unlike phylogenetic trees, which focus on individual shared mutations, this new approach assesses genome-wide co-developing functionalities and hence offers a more fluid view of the 'cloud of variances' that RNA viruses are prone to accumulate. This joint approach concludes that while the current animal models cover the existing viral strains adequately, there is substantial evolutionary activity that is likely not considered by the current models. Based on insights from the non-discrete alignment-free approach and experimental observations, we suggest isolates for future animal models. |*Computational Biology[MESH] |*Disease Outbreaks[MESH] |*Genomics[MESH] |Animals[MESH] |Betacoronavirus/genetics[MESH] |Biological Evolution[MESH] |COVID-19[MESH] |Coronavirus Infections/*epidemiology[MESH] |Disease Models, Animal[MESH] |Humans[MESH] |Pandemics/*prevention & control[MESH] |Phylogeny[MESH] |Pneumonia, Viral/*epidemiology[MESH]Supporting pandemic response using genomics and bioinformatics: A case(epmc).pdf DeepDyve Pubget Overpricing