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10.1186/s13073-015-0189-4 http://scihub22266oqcxt.onion/10.1186/s13073-015-0189-4 C4499940!4499940!26170901     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=26170901&cmd=llinks): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 215 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 211.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Genome+Med 2015 ; 7 (1): ä Nephropedia Template TP {{tp|p=26170901|t=2015. Inferring pathway dysregulation in cancers from multiple types of omic data |pdf=|usr=}}{{26170901}} gab.com Text Inferring pathway dysregulation in cancers from multiple types of omic data JO: Genome Med http://www.kidney.de/pget.php?&tw=1&pmid=26170901 #FOAvip Although in some cases individual genomic aberrations may drive disease development in isolation, a complex interplay among multiple aberrations is common. Accordingly, we developed Gene Set Omic Analysis (GSOA), a bioinformatics tool that can evaluate multiple types and combinations of omic data at the pathway level. GSOA uses machine learning to identify dysregulated pathways and improves upon other methods because of its ability to decipher complex, multigene patterns. We compare GSOA to alternative methods and demonstrate its ability to identify pathways known to play a role in various cancer phenotypes. Software implementing the GSOA method is freely available from https://bitbucket.org/srp33/gsoa.Electronic supplementary material: The online version of this article (doi:10.1186/s13073-015-0189-4) contains supplementary material, which is available to authorized users. Twit Text FOAVip Inferring pathway dysregulation in cancers from multiple types of omic data ????Genome Med http://www.kidney.de/pget.php?&tw=1&pmid=26170901 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26170901 #FOAvip English Wikipedia <ref>{{Cite pmid|26170901}}</ref> Inferring pathway dysregulation in cancers from multiple types of omic data #MMPMID26170901 MacNeil SM; Johnson WE; Li DY; Piccolo SR; Bild AH Genome Med 2015[]; 7 (1): ä PMID26170901show ga Although in some cases individual genomic aberrations may drive disease development in isolation, a complex interplay among multiple aberrations is common. Accordingly, we developed Gene Set Omic Analysis (GSOA), a bioinformatics tool that can evaluate multiple types and combinations of omic data at the pathway level. GSOA uses machine learning to identify dysregulated pathways and improves upon other methods because of its ability to decipher complex, multigene patterns. We compare GSOA to alternative methods and demonstrate its ability to identify pathways known to play a role in various cancer phenotypes. Software implementing the GSOA method is freely available from https://bitbucket.org/srp33/gsoa.Electronic supplementary material: The online version of this article (doi:10.1186/s13073-015-0189-4) contains supplementary material, which is available to authorized users. äInferring pathway dysregulation in cancers from multiple types of omic(epmc).pdf DeepDyve Pubget Overpricing