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10.1158/1078-0432.CCR-12-2093 http://scihub22266oqcxt.onion/10.1158/1078-0432.CCR-12-2093 C3686839!3686839!23430023     free     free     free Warning: file_get_contents(https://eutils.ncbi.nlm.nih.gov/entrez/eutils/elink.fcgi?dbfrom=pubmed&id=23430023&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 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       Clin+Cancer+Res 2013 ; 19 (12): 3114-20 Nephropedia Template TP {{tp|p=23430023|t=2013. Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data |pdf=|usr=}}{{23430023}} gab.com Text Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data JO: Clin Cancer Res http://www.kidney.de/pget.php?&tw=1&pmid=23430023 #FOAvip High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes.How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care ? which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the ?activitome,? help connect genomic events to clinical factors in order to predict the drivers of poor outcome. Twit Text FOAVip Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data ????Clin Cancer Res http://www.kidney.de/pget.php?&tw=1&pmid=23430023 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=23430023 #FOAvip English Wikipedia <ref>{{Cite pmid|23430023}}</ref> Molecular Pathways: Extracting Medical Knowledge from High Throughput Genomic Data #MMPMID23430023 Goldstein T; Paull EO; Ellis MJ; Stuart JM Clin Cancer Res 2013[Jun]; 19 (12): 3114-20 PMID23430023show ga High-throughput genomic data that measures RNA expression, DNA copy number, mutation status and protein levels provide us with insights into the molecular pathway structure of cancer. Genomic lesions (amplifications, deletions, mutations) and epigenetic modifications disrupt biochemical cellular pathways. While the number of possible lesions is vast, different genomic alterations may result in concordant expression and pathway activities, producing common tumor subtypes that share similar phenotypic outcomes.How can these data be translated into medical knowledge that provides prognostic and predictive information? First generation mRNA expression signatures such as Genomic Health's Oncotype DX already provide prognostic information, but do not provide therapeutic guidance beyond the current standard of care ? which is often inadequate in high-risk patients. Rather than building molecular signatures based on gene expression levels, evidence is growing that signatures based on higher-level quantities such as from genetic pathways may provide important prognostic and diagnostic cues. We provide examples of how activities for molecular entities can be predicted from pathway analysis and how the composite of all such activities, referred to here as the ?activitome,? help connect genomic events to clinical factors in order to predict the drivers of poor outcome. äMolecular Pathways: Extracting Medical Knowledge from High Throughput (epmc).pdf DeepDyve Pubget Overpricing