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10.1093/nar/gkab881 http://scihub22266oqcxt.onion/10.1093/nar/gkab881 34634820!8524591!34634820     free     free     free Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 209.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Nucleic+Acids+Res 2022 ; 50 (D1): D867-D874 Nephropedia Template TP {{tp|p=34634820|t=2022. SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues |pdf=|usr=}}{{34634820}} gab.com Text SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues JO: Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34634820 #FOAvip SCovid (http://bio-annotation.cn/scovid) aims at providing a comprehensive resource of single-cell data for exposing molecular characteristics of coronavirus disease 2019 (COVID-19) across 10 human tissues. COVID-19, an epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been found to be accompanied with multiple-organ failure since its first report in Dec 2019. To reveal tissue-specific molecular characteristics, researches regarding to COVID-19 have been carried out widely, especially at single-cell resolution. However, these researches are still relatively independent and scattered, limiting the comprehensive understanding of the impact of virus on diverse tissues. To this end, we developed a single-cell atlas of COVID-19. Firstly we collected 21 single-cell datasets of COVID-19 across 10 human tissues paired with control datasets. Then we constructed a pipeline for the analysis of these datasets to reveal molecular characteristics of COVID-19 based on manually annotated cell types. The current version of SCovid documents 1 042 227 single cells of 21 single-cell datasets across 10 human tissues, 11 713 stably expressed genes and 3778 significant differentially expressed genes (DEGs). SCovid provides a user-friendly interface for browsing, searching, visualizing and downloading all detailed information. Twit Text FOAVip SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues ????Nucleic Acids Res http://www.kidney.de/pget.php?&tw=1&pmid=34634820 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34634820 #FOAvip English Wikipedia <ref>{{Cite pmid|34634820}}</ref> SCovid: single-cell atlases for exposing molecular characteristics of COVID-19 across 10 human tissues #MMPMID34634820 Qi C; Wang C; Zhao L; Zhu Z; Wang P; Zhang S; Cheng L; Zhang X Nucleic Acids Res 2022[Jan]; 50 (D1): D867-D874 PMID34634820show ga SCovid (http://bio-annotation.cn/scovid) aims at providing a comprehensive resource of single-cell data for exposing molecular characteristics of coronavirus disease 2019 (COVID-19) across 10 human tissues. COVID-19, an epidemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been found to be accompanied with multiple-organ failure since its first report in Dec 2019. To reveal tissue-specific molecular characteristics, researches regarding to COVID-19 have been carried out widely, especially at single-cell resolution. However, these researches are still relatively independent and scattered, limiting the comprehensive understanding of the impact of virus on diverse tissues. To this end, we developed a single-cell atlas of COVID-19. Firstly we collected 21 single-cell datasets of COVID-19 across 10 human tissues paired with control datasets. Then we constructed a pipeline for the analysis of these datasets to reveal molecular characteristics of COVID-19 based on manually annotated cell types. The current version of SCovid documents 1 042 227 single cells of 21 single-cell datasets across 10 human tissues, 11 713 stably expressed genes and 3778 significant differentially expressed genes (DEGs). SCovid provides a user-friendly interface for browsing, searching, visualizing and downloading all detailed information. |*Databases, Factual[MESH] |*Single-Cell Analysis[MESH] |COVID-19/genetics/*pathology[MESH] |Humans[MESH] |Transcriptome[MESH]SCovid: single-cell atlases for exposing molecular characteristics of (epmc).pdf DeepDyve Pubget Overpricing