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10.1186/s41236-018-0008-0 http://scihub22266oqcxt.onion/10.1186/s41236-018-0008-0 C5876693!5876693!29623956     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       Cancer+Converg 2018 ; 2 (1): ä Nephropedia Template TP {{tp|p=29623956|t=2018. Cancer dormancy and criticality from a game theory perspective |pdf=|usr=}}{{29623956}} gab.com Text Cancer dormancy and criticality from a game theory perspective JO: Cancer Converg http://www.kidney.de/pget.php?&tw=1&pmid=29623956 #FOAvip Background: The physics of cancer dormancy, the time between initial cancer treatment and re-emergence after a protracted period, is a puzzle. Cancer cells interact with host cells via complex, non-linear population dynamics, which can lead to very non-intuitive but perhaps deterministic and understandable progression dynamics of cancer and dormancy. Results: We explore here the dynamics of host-cancer cell populations in the presence of (1) payoffs gradients and (2) perturbations due to cell migration. Conclusions: We determine to what extent the time-dependence of the populations can be quantitively understood in spite of the underlying complexity of the individual agents and model the phenomena of dormancy. Twit Text FOAVip Cancer dormancy and criticality from a game theory perspective ????Cancer Converg http://www.kidney.de/pget.php?&tw=1&pmid=29623956 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=29623956 #FOAvip English Wikipedia <ref>{{Cite pmid|29623956}}</ref> Cancer dormancy and criticality from a game theory perspective #MMPMID29623956 Wu A; Liao D; Kirilin V; Lin KC; Torga G; Qu J; Liu L; Sturm JC; Pienta K; Austin R Cancer Converg 2018[]; 2 (1): ä PMID29623956show ga Background: The physics of cancer dormancy, the time between initial cancer treatment and re-emergence after a protracted period, is a puzzle. Cancer cells interact with host cells via complex, non-linear population dynamics, which can lead to very non-intuitive but perhaps deterministic and understandable progression dynamics of cancer and dormancy. Results: We explore here the dynamics of host-cancer cell populations in the presence of (1) payoffs gradients and (2) perturbations due to cell migration. Conclusions: We determine to what extent the time-dependence of the populations can be quantitively understood in spite of the underlying complexity of the individual agents and model the phenomena of dormancy. äCancer dormancy and criticality from a game theory perspective (epmc).pdf DeepDyve Pubget Overpricing