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10.1155/2017/2954351 http://scihub22266oqcxt.onion/10.1155/2017/2954351 C5390606!5390606!28466007     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Biomed+Res+Int 2017 ; 2017 (ä): ä Nephropedia Template TP {{tp|p=28466007|t=2017. Dissect the Dynamic Molecular Circuits of Cell Cycle Control through Network Evolution Model |pdf=|usr=}}{{28466007}} gab.com Text Dissect the Dynamic Molecular Circuits of Cell Cycle Control through Network Evolution Model JO: Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=28466007 #FOAvip The molecular circuits of cell cycle control serve as a key hub to integrate from endogenous and environmental signals into a robust biological decision driving cell growth and division. Dysfunctional cell cycle control is highlighted in a wide spectrum of human cancers. More importantly the mainstay anticancer treatment such as radiation therapy and chemotherapy targets the hallmark of uncontrolled cell proliferation in cancer cells by causing DNA damage, cell cycle arrest, and cell death. Given the functional importance of cell cycle control, the regulatory mechanisms that drive the cell division have been extensively investigated in a huge number of studies by conventional single-gene approaches. However the complexity of cell cycle control renders a significant barrier to understand its function at a network level. In this study, we used mathematical modeling through modern graph theory and differential equation systems. We believe our network evolution model can help us understand the dynamic cell cycle control in tumor evolution and optimizing dosing schedules for radiation therapy and chemotherapy targeting cell cycle. Twit Text FOAVip Dissect the Dynamic Molecular Circuits of Cell Cycle Control through Network Evolution Model ????Biomed Res Int http://www.kidney.de/pget.php?&tw=1&pmid=28466007 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=28466007 #FOAvip English Wikipedia <ref>{{Cite pmid|28466007}}</ref> Dissect the Dynamic Molecular Circuits of Cell Cycle Control through Network Evolution Model #MMPMID28466007 Peng Y; Scott P; Tao R; Wang H; Wu Y; Peng G Biomed Res Int 2017[]; 2017 (ä): ä PMID28466007show ga The molecular circuits of cell cycle control serve as a key hub to integrate from endogenous and environmental signals into a robust biological decision driving cell growth and division. Dysfunctional cell cycle control is highlighted in a wide spectrum of human cancers. More importantly the mainstay anticancer treatment such as radiation therapy and chemotherapy targets the hallmark of uncontrolled cell proliferation in cancer cells by causing DNA damage, cell cycle arrest, and cell death. Given the functional importance of cell cycle control, the regulatory mechanisms that drive the cell division have been extensively investigated in a huge number of studies by conventional single-gene approaches. However the complexity of cell cycle control renders a significant barrier to understand its function at a network level. In this study, we used mathematical modeling through modern graph theory and differential equation systems. We believe our network evolution model can help us understand the dynamic cell cycle control in tumor evolution and optimizing dosing schedules for radiation therapy and chemotherapy targeting cell cycle. äDissect the Dynamic Molecular Circuits of Cell Cycle Control through N(epmc).pdf DeepDyve Pubget Overpricing