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10.1016/j.ijbiomac.2021.11.124 http://scihub22266oqcxt.onion/10.1016/j.ijbiomac.2021.11.124 34826456!8610562!34826456     free     free     free 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 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 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 245.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Biol+Macromol 2022 ; 194 (ä): 770-780 Nephropedia Template TP {{tp|p=34826456|t=2022. Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome |pdf=|usr=}}{{34826456}} gab.com Text Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome JO: Int J Biol Macromol http://www.kidney.de/pget.php?&tw=1&pmid=34826456 #FOAvip The molecular mechanisms underlying the pathogenesis of COVID-19 have not been fully discovered. This study aims to decipher potentially hidden parts of the pathogenesis of COVID-19, potential novel drug targets, and identify potential drug candidates. Two gene expression profiles were analyzed, and overlapping differentially expressed genes (DEGs) were selected for which top enriched transcription factors and kinases were identified, and pathway analysis was performed. Protein-protein interaction (PPI) of DEGs was constructed, hub genes were identified, and module analysis was also performed. DGIdb database was used to identify drugs for the potential targets (hub genes and the most enriched transcription factors and kinases for DEGs). A drug-potential target network was constructed, and drugs were ranked according to the degree. L1000FDW was used to identify drugs that can reverse transcriptional profiles of COVID-19. We identified drugs currently in clinical trials, others predicted by different methods, and novel potential drug candidates Entrectinib, Omeprazole, and Exemestane for combating COVID-19. Besides the well-known pathogenic pathways, it was found that axon guidance is a potential pathogenic pathway. Sema7A, which may exacerbate hypercytokinemia, is considered a potential novel drug target. Another potential novel pathway is related to TINF2 overexpression, which may induce potential telomere dysfunction and damage DNA that may exacerbate lung fibrosis. This study identified new potential insights regarding COVID-19 pathogenesis and treatment, which might help us improve our understanding of the mechanisms of COVID-19. Twit Text FOAVip Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome ????Int J Biol Macromol http://www.kidney.de/pget.php?&tw=1&pmid=34826456 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34826456 #FOAvip English Wikipedia <ref>{{Cite pmid|34826456}}</ref> Identifying potential novel insights for COVID-19 pathogenesis and therapeutics using an integrated bioinformatics analysis of host transcriptome #MMPMID34826456 El-Aarag SA; Mahmoud A; ElHefnawi M Int J Biol Macromol 2022[Jan]; 194 (ä): 770-780 PMID34826456show ga The molecular mechanisms underlying the pathogenesis of COVID-19 have not been fully discovered. This study aims to decipher potentially hidden parts of the pathogenesis of COVID-19, potential novel drug targets, and identify potential drug candidates. Two gene expression profiles were analyzed, and overlapping differentially expressed genes (DEGs) were selected for which top enriched transcription factors and kinases were identified, and pathway analysis was performed. Protein-protein interaction (PPI) of DEGs was constructed, hub genes were identified, and module analysis was also performed. DGIdb database was used to identify drugs for the potential targets (hub genes and the most enriched transcription factors and kinases for DEGs). A drug-potential target network was constructed, and drugs were ranked according to the degree. L1000FDW was used to identify drugs that can reverse transcriptional profiles of COVID-19. We identified drugs currently in clinical trials, others predicted by different methods, and novel potential drug candidates Entrectinib, Omeprazole, and Exemestane for combating COVID-19. Besides the well-known pathogenic pathways, it was found that axon guidance is a potential pathogenic pathway. Sema7A, which may exacerbate hypercytokinemia, is considered a potential novel drug target. Another potential novel pathway is related to TINF2 overexpression, which may induce potential telomere dysfunction and damage DNA that may exacerbate lung fibrosis. This study identified new potential insights regarding COVID-19 pathogenesis and treatment, which might help us improve our understanding of the mechanisms of COVID-19. |*Transcriptome[MESH] |COVID-19/*virology[MESH] |Computational Biology/*methods[MESH] |Databases, Factual[MESH] |Humans[MESH]Identifying potential novel insights for COVID-19 pathogenesis and the(epmc).pdf DeepDyve Pubget Overpricing