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10.1016/j.patter.2021.100396 http://scihub22266oqcxt.onion/10.1016/j.patter.2021.100396 34778851!8576113!34778851     free     free     free Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 213.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\34778851.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Patterns+(N+Y) 2022 ; 3 (1): 100396 Nephropedia Template TP {{tp|p=34778851|t=2022. Machine learning and network medicine approaches for drug repositioning for COVID-19 |pdf=|usr=}}{{34778851}} gab.com Text Machine learning and network medicine approaches for drug repositioning for COVID-19 JO: Patterns (N Y) http://www.kidney.de/pget.php?&tw=1&pmid=34778851 #FOAvip We present two machine learning approaches for drug repurposing. While we have developed them for COVID-19, they are disease-agnostic. The two methodologies are complementary, targeting SARS-CoV-2 and host factors, respectively. Our first approach consists of a matrix factorization algorithm to rank broad-spectrum antivirals. Our second approach, based on network medicine, uses graph kernels to rank drugs according to the perturbation they induce on a subnetwork of the human interactome that is crucial for SARS-CoV-2 infection/replication. Our experiments show that our top predicted broad-spectrum antivirals include drugs indicated for compassionate use in COVID-19 patients; and that the ranking obtained by our kernel-based approach aligns with experimental data. Finally, we present the COVID-19 repositioning explorer (CoREx), an interactive online tool to explore the interplay between drugs and SARS-CoV-2 host proteins in the context of biological networks, protein function, drug clinical use, and Connectivity Map. CoREx is freely available at: https://paccanarolab.org/corex/. Twit Text FOAVip Machine learning and network medicine approaches for drug repositioning for COVID-19 ????Patterns (N Y) http://www.kidney.de/pget.php?&tw=1&pmid=34778851 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34778851 #FOAvip English Wikipedia <ref>{{Cite pmid|34778851}}</ref> Machine learning and network medicine approaches for drug repositioning for COVID-19 #MMPMID34778851 Santos SS; Torres M; Galeano D; Sanchez MDM; Cernuzzi L; Paccanaro A Patterns (N Y) 2022[Jan]; 3 (1): 100396 PMID34778851show ga We present two machine learning approaches for drug repurposing. While we have developed them for COVID-19, they are disease-agnostic. The two methodologies are complementary, targeting SARS-CoV-2 and host factors, respectively. Our first approach consists of a matrix factorization algorithm to rank broad-spectrum antivirals. Our second approach, based on network medicine, uses graph kernels to rank drugs according to the perturbation they induce on a subnetwork of the human interactome that is crucial for SARS-CoV-2 infection/replication. Our experiments show that our top predicted broad-spectrum antivirals include drugs indicated for compassionate use in COVID-19 patients; and that the ranking obtained by our kernel-based approach aligns with experimental data. Finally, we present the COVID-19 repositioning explorer (CoREx), an interactive online tool to explore the interplay between drugs and SARS-CoV-2 host proteins in the context of biological networks, protein function, drug clinical use, and Connectivity Map. CoREx is freely available at: https://paccanarolab.org/corex/. äMachine learning and network medicine approaches for drug repositionin(epmc).pdf DeepDyve Pubget Overpricing