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10.1016/j.medidd.2021.100090 http://scihub22266oqcxt.onion/10.1016/j.medidd.2021.100090 33817623!8008783!33817623     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       Med+Drug+Discov 2021 ; 10 (ä): 100090 Nephropedia Template TP {{tp|p=33817623|t=2021. Network bioinformatics analysis provides insight into drug repurposing for COVID-19 |pdf=|usr=}}{{33817623}} gab.com Text Network bioinformatics analysis provides insight into drug repurposing for COVID-19 JO: Med Drug Discov http://www.kidney.de/pget.php?&tw=1&pmid=33817623 #FOAvip The COVID-19 disease caused by the SARS-CoV-2 virus is a health crisis worldwide. While developing novel drugs and vaccines is long, repurposing existing drugs against COVID-19 can yield treatments with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter clinical trials. In this study, we present a novel network-based drug repurposing platform to identify candidates for the treatment of COVID-19. At the time of the initial outbreak, knowledge about SARS-CoV-2 was lacking, but based on its similarity with other viruses, we sought to identify repurposing candidates to be tested rapidly at the clinical or preclinical levels. We first analyzed the genome sequence of SARS-CoV-2 and confirmed SARS as the closest virus by genome similarity, followed by MERS and other human coronaviruses. Using text mining and database searches, we obtained 34 COVID-19-related genes to seed the construction of a molecular network where our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules, and 78 drugs to repurpose. Based on clinical knowledge, we re-prioritized 30 potentially repurposable drugs against COVID-19 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide). Our work shows how in silico repurposing analyses can yield testable candidates to accelerate the response to novel disease outbreaks. Twit Text FOAVip Network bioinformatics analysis provides insight into drug repurposing for COVID-19 ????Med Drug Discov http://www.kidney.de/pget.php?&tw=1&pmid=33817623 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33817623 #FOAvip English Wikipedia <ref>{{Cite pmid|33817623}}</ref> Network bioinformatics analysis provides insight into drug repurposing for COVID-19 #MMPMID33817623 Li X; Yu J; Zhang Z; Ren J; Peluffo AE; Zhang W; Zhao Y; Wu J; Yan K; Cohen D; Wang W Med Drug Discov 2021[Jun]; 10 (ä): 100090 PMID33817623show ga The COVID-19 disease caused by the SARS-CoV-2 virus is a health crisis worldwide. While developing novel drugs and vaccines is long, repurposing existing drugs against COVID-19 can yield treatments with known preclinical, pharmacokinetic, pharmacodynamic, and toxicity profiles, which can rapidly enter clinical trials. In this study, we present a novel network-based drug repurposing platform to identify candidates for the treatment of COVID-19. At the time of the initial outbreak, knowledge about SARS-CoV-2 was lacking, but based on its similarity with other viruses, we sought to identify repurposing candidates to be tested rapidly at the clinical or preclinical levels. We first analyzed the genome sequence of SARS-CoV-2 and confirmed SARS as the closest virus by genome similarity, followed by MERS and other human coronaviruses. Using text mining and database searches, we obtained 34 COVID-19-related genes to seed the construction of a molecular network where our module detection and drug prioritization algorithms identified 24 disease-related human pathways, five modules, and 78 drugs to repurpose. Based on clinical knowledge, we re-prioritized 30 potentially repurposable drugs against COVID-19 (including pseudoephedrine, andrographolide, chloroquine, abacavir, and thalidomide). Our work shows how in silico repurposing analyses can yield testable candidates to accelerate the response to novel disease outbreaks. äNetwork bioinformatics analysis provides insight into drug repurposing(epmc).pdf DeepDyve Pubget Overpricing