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10.1038/s41598-020-74705-6 http://scihub22266oqcxt.onion/10.1038/s41598-020-74705-6 33077837!7573595!33077837     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 243.2 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\33077837.jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Sci+Rep 2020 ; 10 (1): 17628 Nephropedia Template TP {{tp|p=33077837|t=2020. Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method |pdf=|usr=}}{{33077837}} gab.com Text Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method JO: Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33077837 #FOAvip Genes are organized in functional modules (or pathways), thus their action and their dysregulation in diseases may be better understood by the identification of the modules most affected by the disease (aka disease modules, or active subnetworks). We describe how an algorithm based on the Core&Peel method is used to detect disease modules in co-expression networks of genes. We first validate Core&Peel for the general task of functional module detection by comparison with 42 methods participating in the Disease Module Identification DREAM challenge. Next, we use four specific disease test cases (colorectal cancer, prostate cancer, asthma, and rheumatoid arthritis), four state-of-the-art algorithms (ModuleDiscoverer, Degas, KeyPathwayMiner, and ClustEx), and several pathway databases to validate the proposed algorithm. Core&Peel is the only method able to find significant associations of the predicted disease module with known validated relevant pathways for all four diseases. Moreover, for the two cancer datasets, Core&Peel detects further eight relevant pathways not discovered by the other methods used in the comparative analysis. Finally, we apply Core&Peel and other methods to explore the transcriptional response of human cells to SARS-CoV-2 infection, finding supporting evidence for drug repositioning efforts at a pre-clinical level. Twit Text FOAVip Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method ????Sci Rep http://www.kidney.de/pget.php?&tw=1&pmid=33077837 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=33077837 #FOAvip English Wikipedia <ref>{{Cite pmid|33077837}}</ref> Finding disease modules for cancer and COVID-19 in gene co-expression networks with the Core&Peel method #MMPMID33077837 Lucchetta M; Pellegrini M Sci Rep 2020[Oct]; 10 (1): 17628 PMID33077837show ga Genes are organized in functional modules (or pathways), thus their action and their dysregulation in diseases may be better understood by the identification of the modules most affected by the disease (aka disease modules, or active subnetworks). We describe how an algorithm based on the Core&Peel method is used to detect disease modules in co-expression networks of genes. We first validate Core&Peel for the general task of functional module detection by comparison with 42 methods participating in the Disease Module Identification DREAM challenge. Next, we use four specific disease test cases (colorectal cancer, prostate cancer, asthma, and rheumatoid arthritis), four state-of-the-art algorithms (ModuleDiscoverer, Degas, KeyPathwayMiner, and ClustEx), and several pathway databases to validate the proposed algorithm. Core&Peel is the only method able to find significant associations of the predicted disease module with known validated relevant pathways for all four diseases. Moreover, for the two cancer datasets, Core&Peel detects further eight relevant pathways not discovered by the other methods used in the comparative analysis. Finally, we apply Core&Peel and other methods to explore the transcriptional response of human cells to SARS-CoV-2 infection, finding supporting evidence for drug repositioning efforts at a pre-clinical level. |*Algorithms[MESH] |COVID-19[MESH] |Coronavirus Infections/genetics/*pathology[MESH] |Databases, Genetic[MESH] |Drug Repositioning[MESH] |Gene Expression Profiling[MESH] |Gene Ontology[MESH] |Gene Regulatory Networks/*genetics[MESH] |Genome-Wide Association Study[MESH] |Humans[MESH] |Neoplasms/genetics/*pathology[MESH] |Pandemics[MESH] |Pneumonia, Viral/genetics/*pathology[MESH]Finding disease modules for cancer and COVID-19 in gene co-expression (epmc).pdf DeepDyve Pubget Overpricing