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10.1038/nmeth.4463 http://scihub22266oqcxt.onion/10.1038/nmeth.4463 C5937676!5937676 !28991892     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 Warning: imagejpeg(C:\Inetpub\vhosts\kidney.de\httpdocs\phplern\28991892 .jpg): Failed to open stream: No such file or directory in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 117       Nat+Methods 2017 ; 14 (11 ): 1083-1086 Nephropedia Template TP {{tp|p=28991892 |t=2017. SCENIC: single-cell regulatory network inference and clustering |pdf=|usr=}}{{28991892 }} gab.com Text SCENIC: single-cell regulatory network inference and clustering JO: Nat Methods http://www.kidney.de/pget.php?&tw=1&pmid=28991892 #FOAvip We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic.aertslab.org). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity. Twit Text FOAVip SCENIC: single-cell regulatory network inference and clustering ????Nat Methods http://www.kidney.de/pget.php?&tw=1&pmid=28991892 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28991892 #FOAvip English Wikipedia <ref>{{Cite pmid|28991892 }}</ref> SCENIC: single-cell regulatory network inference and clustering #MMPMID28991892 Aibar S ; González-Blas CB ; Moerman T ; Huynh-Thu VA ; Imrichova H ; Hulselmans G ; Rambow F ; Marine JC ; Geurts P ; Aerts J ; van den Oord J ; Atak ZK ; Wouters J ; Aerts S Nat Methods 2017[Nov]; 14 (11 ): 1083-1086 PMID28991892 show ga We present SCENIC, a computational method for simultaneous gene regulatory network reconstruction and cell-state identification from single-cell RNA-seq data (http://scenic.aertslab.org). On a compendium of single-cell data from tumors and brain, we demonstrate that cis-regulatory analysis can be exploited to guide the identification of transcription factors and cell states. SCENIC provides critical biological insights into the mechanisms driving cellular heterogeneity. |*Gene Regulatory Networks [MESH] |*Single-Cell Analysis [MESH] |Algorithms [MESH] |Animals [MESH] |Brain/metabolism [MESH] |Cluster Analysis [MESH] |Gene Expression Profiling [MESH] |Humans [MESH]SCENIC: single-cell regulatory network inference and clustering (epmc).pdf DeepDyve Pubget Overpricing