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10.3390/pathogens11020259 http://scihub22266oqcxt.onion/10.3390/pathogens11020259 35215201!8874499!35215201     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 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 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 267.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Pathogens 2022 ; 11 (2): ä Nephropedia Template TP {{tp|p=35215201|t=2022. Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods |pdf=|usr=}}{{35215201}} gab.com Text Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods JO: Pathogens http://www.kidney.de/pget.php?&tw=1&pmid=35215201 #FOAvip Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2. Twit Text FOAVip Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods ????Pathogens http://www.kidney.de/pget.php?&tw=1&pmid=35215201 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=35215201 #FOAvip English Wikipedia <ref>{{Cite pmid|35215201}}</ref> Deciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Channels Using Machine-Learning-Based Methods #MMPMID35215201 Munjal NS; Sapra D; Parthasarathi KTS; Goyal A; Pandey A; Banerjee M; Sharma J Pathogens 2022[Feb]; 11 (2): ä PMID35215201show ga Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is accountable for the protracted COVID-19 pandemic. Its high transmission rate and pathogenicity led to health emergencies and economic crisis. Recent studies pertaining to the understanding of the molecular pathogenesis of SARS-CoV-2 infection exhibited the indispensable role of ion channels in viral infection inside the host. Moreover, machine learning (ML)-based algorithms are providing a higher accuracy for host-SARS-CoV-2 protein-protein interactions (PPIs). In this study, PPIs of SARS-CoV-2 proteins with human ion channels (HICs) were trained on the PPI-MetaGO algorithm. PPI networks (PPINs) and a signaling pathway map of HICs with SARS-CoV-2 proteins were generated. Additionally, various U.S. food and drug administration (FDA)-approved drugs interacting with the potential HICs were identified. The PPIs were predicted with 82.71% accuracy, 84.09% precision, 84.09% sensitivity, 0.89 AUC-ROC, 65.17% Matthews correlation coefficient score (MCC) and 84.09% F1 score. Several host pathways were found to be altered, including calcium signaling and taste transduction pathway. Potential HICs could serve as an initial set to the experimentalists for further validation. The study also reinforces the drug repurposing approach for the development of host directed antiviral drugs that may provide a better therapeutic management strategy for infection caused by SARS-CoV-2. äDeciphering the Interactions of SARS-CoV-2 Proteins with Human Ion Cha(epmc).pdf DeepDyve Pubget Overpricing