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10.1158/0008-5472.CAN-16-0512 http://scihub22266oqcxt.onion/10.1158/0008-5472.CAN-16-0512 C5410377!5410377!28087598     free     free     free Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 225.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 259.2 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Cancer+Res 2017 ; 77 (7): 1575-85 Nephropedia Template TP {{tp|p=28087598|t=2017. Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells |pdf=|usr=}}{{28087598}} gab.com Text Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells JO: Cancer Res http://www.kidney.de/pget.php?&tw=1&pmid=28087598 #FOAvip Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate non-intuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed model comprised of an ensemble of networks using multi-dimensional data from cell line models of cell cycle arrest caused by inhibition of MEK1/2. Through simulation of reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 out 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NF?B and AP-1 sites and sensitized cells to TNF-Related Apoptosis-Inducing Ligand (TRAIL)-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NF?B and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFkB signaling. Twit Text FOAVip Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells ????Cancer Res http://www.kidney.de/pget.php?&tw=1&pmid=28087598 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28087598 #FOAvip English Wikipedia <ref>{{Cite pmid|28087598}}</ref> Bayesian network inference modeling identifies TRIB1 as a novel regulator of cell cycle progression and survival in cancer cells #MMPMID28087598 Gendelman R; Xing H; Mirzoeva OK; Sarde P; Curtis C; Feiler HS; McDonagh P; Gray JW; Khalil I; Korn WM Cancer Res 2017[Apr]; 77 (7): 1575-85 PMID28087598show ga Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate non-intuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed model comprised of an ensemble of networks using multi-dimensional data from cell line models of cell cycle arrest caused by inhibition of MEK1/2. Through simulation of reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 out 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NF?B and AP-1 sites and sensitized cells to TNF-Related Apoptosis-Inducing Ligand (TRAIL)-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NF?B and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFkB signaling. äBayesian network inference modeling identifies TRIB1 as a novel regula(epmc).pdf DeepDyve Pubget Overpricing