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10.1016/j.xpro.2021.100873 http://scihub22266oqcxt.onion/10.1016/j.xpro.2021.100873 34746856!8551262!34746856     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       STAR+Protoc 2021 ; 2 (4): 100873 Nephropedia Template TP {{tp|p=34746856|t=2021. Computational workflow for functional characterization of COVID-19 through secondary data analysis |pdf=|usr=}}{{34746856}} gab.com Text Computational workflow for functional characterization of COVID-19 through secondary data analysis JO: STAR Protoc http://www.kidney.de/pget.php?&tw=1&pmid=34746856 #FOAvip Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes. We present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein interactions, single-cell RNA-seq markers, and phenotype-genotype associations to identify functional feature complexes. These feature modules represent a higher order multifeatured machines collectively working toward common pathophysiological goals. We apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases. For complete details on the use and execution of this protocol, please refer to Ghandikota et al. (2021). Twit Text FOAVip Computational workflow for functional characterization of COVID-19 through secondary data analysis ????STAR Protoc http://www.kidney.de/pget.php?&tw=1&pmid=34746856 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=34746856 #FOAvip English Wikipedia <ref>{{Cite pmid|34746856}}</ref> Computational workflow for functional characterization of COVID-19 through secondary data analysis #MMPMID34746856 Ghandikota S; Sharma M; Jegga AG STAR Protoc 2021[Dec]; 2 (4): 100873 PMID34746856show ga Standard transcriptomic analyses cannot fully capture the molecular mechanisms underlying disease pathophysiology and outcomes. We present a computational heterogeneous data integration and mining protocol that combines transcriptional signatures from multiple model systems, protein-protein interactions, single-cell RNA-seq markers, and phenotype-genotype associations to identify functional feature complexes. These feature modules represent a higher order multifeatured machines collectively working toward common pathophysiological goals. We apply this protocol for functional characterization of COVID-19, but it could be applied to many other diseases. For complete details on the use and execution of this protocol, please refer to Ghandikota et al. (2021). |*Data Analysis[MESH] |*Software[MESH] |*Transcriptome[MESH] |*Workflow[MESH] |COVID-19/*diagnosis/genetics/virology[MESH] |Computational Biology/*methods[MESH] |Humans[MESH]Computational workflow for functional characterization of COVID-19 thr(epmc).pdf DeepDyve Pubget Overpricing