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10.1038/s41540-017-0009-0 http://scihub22266oqcxt.onion/10.1038/s41540-017-0009-0 C5445628!5445628!28649437     free     free     free Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 231.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       NPJ+Syst+Biol+Appl 2017 ; 3 (ä): ä Nephropedia Template TP {{tp|p=28649437|t=2017. Integrating personalized gene expression profiles into predictive disease-associated gene pools |pdf=|usr=}}{{28649437}} gab.com Text Integrating personalized gene expression profiles into predictive disease-associated gene pools JO: NPJ Syst Biol Appl http://www.kidney.de/pget.php?&tw=1&pmid=28649437 #FOAvip Gene expression data are routinely used to identify genes that on average exhibit different expression levels between a case and a control group. Yet, very few of such differentially expressed genes are detectably perturbed in individual patients. Here, we develop a framework to construct personalized perturbation profiles for individual subjects, identifying the set of genes that are significantly perturbed in each individual. This allows us to characterize the heterogeneity of the molecular manifestations of complex diseases by quantifying the expression-level similarities and differences among patients with the same phenotype. We show that despite the high heterogeneity of the individual perturbation profiles, patients with asthma, Parkinson and Huntington?s disease share a broadpool of sporadically disease-associated genes, and that individuals with statistically significant overlap with this pool have a 80?100% chance of being diagnosed with the disease. The developed framework opens up the possibility to apply gene expression data in the context of precision medicine, with important implications for biomarker identification, drug development, diagnosis and treatment. Twit Text FOAVip Integrating personalized gene expression profiles into predictive disease-associated gene pools ????NPJ Syst Biol Appl http://www.kidney.de/pget.php?&tw=1&pmid=28649437 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28649437 #FOAvip English Wikipedia <ref>{{Cite pmid|28649437}}</ref> Integrating personalized gene expression profiles into predictive disease-associated gene pools #MMPMID28649437 Menche J; Guney E; Sharma A; Branigan PJ; Loza MJ; Baribaud F; Dobrin R; Barabási AL NPJ Syst Biol Appl 2017[]; 3 (ä): ä PMID28649437show ga Gene expression data are routinely used to identify genes that on average exhibit different expression levels between a case and a control group. Yet, very few of such differentially expressed genes are detectably perturbed in individual patients. Here, we develop a framework to construct personalized perturbation profiles for individual subjects, identifying the set of genes that are significantly perturbed in each individual. This allows us to characterize the heterogeneity of the molecular manifestations of complex diseases by quantifying the expression-level similarities and differences among patients with the same phenotype. We show that despite the high heterogeneity of the individual perturbation profiles, patients with asthma, Parkinson and Huntington?s disease share a broadpool of sporadically disease-associated genes, and that individuals with statistically significant overlap with this pool have a 80?100% chance of being diagnosed with the disease. The developed framework opens up the possibility to apply gene expression data in the context of precision medicine, with important implications for biomarker identification, drug development, diagnosis and treatment. äIntegrating personalized gene expression profiles into predictive dise(epmc).pdf DeepDyve Pubget Overpricing