Use my Search Websuite to scan PubMed, PMCentral, Journal Hosts and Journal Archives, FullText. Kick-your-searchterm to multiple Engines kick-your-query now !>

A dictionary by aggregated review articles of nephrology, medicine and the life sciences Your one-stop-run pathway from word to the immediate pdf of peer-reviewed on-topic knowledge.

10.1093/molbev/msaa284 http://scihub22266oqcxt.onion/10.1093/molbev/msaa284 33316043!7665608!33316043     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       Mol+Biol+Evol 2021 ; 38 (4): 1608-1613 Nephropedia Template TP {{tp|p=33316043|t=2021. A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages |pdf=|usr=}}{{33316043}} gab.com Text A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages JO: Mol Biol Evol http://www.kidney.de/pget.php?&tw=1&pmid=33316043 #FOAvip Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement. Twit Text FOAVip A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages ????Mol Biol Evol http://www.kidney.de/pget.php?&tw=1&pmid=33316043 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33316043 #FOAvip English Wikipedia <ref>{{Cite pmid|33316043}}</ref> A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal History and Dynamics of SARS-CoV-2 Lineages #MMPMID33316043 Dellicour S; Durkin K; Hong SL; Vanmechelen B; Marti-Carreras J; Gill MS; Meex C; Bontems S; Andre E; Gilbert M; Walker C; Maio N; Faria NR; Hadfield J; Hayette MP; Bours V; Wawina-Bokalanga T; Artesi M; Baele G; Maes P Mol Biol Evol 2021[Apr]; 38 (4): 1608-1613 PMID33316043show ga Since the start of the COVID-19 pandemic, an unprecedented number of genomic sequences of SARS-CoV-2 have been generated and shared with the scientific community. The unparalleled volume of available genetic data presents a unique opportunity to gain real-time insights into the virus transmission during the pandemic, but also a daunting computational hurdle if analyzed with gold-standard phylogeographic approaches. To tackle this practical limitation, we here describe and apply a rapid analytical pipeline to analyze the spatiotemporal dispersal history and dynamics of SARS-CoV-2 lineages. As a proof of concept, we focus on the Belgian epidemic, which has had one of the highest spatial densities of available SARS-CoV-2 genomes. Our pipeline has the potential to be quickly applied to other countries or regions, with key benefits in complementing epidemiological analyses in assessing the impact of intervention measures or their progressive easement. |*Genome, Viral[MESH] |*Phylogeography[MESH] |Belgium[MESH] |COVID-19/epidemiology/*transmission/*virology[MESH] |Evolution, Molecular[MESH] |Genomics[MESH] |Humans[MESH] |Likelihood Functions[MESH] |Mutation[MESH] |Patient Isolation[MESH] |Phylogeny[MESH] |Physical Distancing[MESH] |SARS-CoV-2/*genetics[MESH] |Spatio-Temporal Analysis[MESH]A Phylodynamic Workflow to Rapidly Gain Insights into the Dispersal Hi(epmc).pdf DeepDyve Pubget Overpricing