%0 Book Section %1 statphys23_0872 %A Artyomov, M.N. %A Das, J. %A Kardar, M. %A Chakraborty, A.K. %B Abstract Book of the XXIII IUPAP International Conference on Statistical Physics %C Genova, Italy %D 2007 %E Pietronero, Luciano %E Loreto, Vittorio %E Zapperi, Stefano %K antagonism bifurcation gillespie monte-carlo scaling statphys23 stochastic t-cell topic-10 %T Purely Stochastic Bifurcations in Cell Signalling %U http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=872 %X We consider a simple kinetic model motivated by signaling events occurring during T-cell activation. Deterministic analysis of the model gives a unique steady-state for all the reaction parameters, while numerical solution of the corresponding master equations (Gillespie Monte-Carlo) shows bimodal behavior in specific regimes of the reaction parameters. Scaling behavior of the signal output with stimulus quality is shown to be different in deterministic (monostable) and in stochastically bimodal regimes. In order to gain further insight into this type of stochastic bifurcation we consider a simplified model, which captures all the essential characteristics of larger model. This model consists of three reactions and is exactly solvable both for the deterministic and the stochastic cases. This model also has a single deterministic fixed point for all values of parameters, but solution of master equation exhibits bimodal behavior in certain range of parameter. Scaling behavior of the deterministic is studied analytically in limiting regimes and shown to be distinct for deterministic and stochastic cases. General principles obtained from these models are applied to understand the basic mechanisms underlying the phenomenon of antagonism in T-cell signaling.

@incollection{statphys23_0872, abstract = {We consider a simple kinetic model motivated by signaling events occurring during T-cell activation. Deterministic analysis of the model gives a unique steady-state for all the reaction parameters, while numerical solution of the corresponding master equations (Gillespie Monte-Carlo) shows bimodal behavior in specific regimes of the reaction parameters. Scaling behavior of the signal output with stimulus quality is shown to be different in deterministic (monostable) and in stochastically bimodal regimes. In order to gain further insight into this type of stochastic bifurcation we consider a simplified model, which captures all the essential characteristics of larger model. This model consists of three reactions and is exactly solvable both for the deterministic and the stochastic cases. This model also has a single deterministic fixed point for all values of parameters, but solution of master equation exhibits bimodal behavior in certain range of parameter. Scaling behavior of the deterministic is studied analytically in limiting regimes and shown to be distinct for deterministic and stochastic cases. General principles obtained from these models are applied to understand the basic mechanisms underlying the phenomenon of antagonism in T-cell signaling.}, added-at = {2007-06-20T10:16:09.000+0200}, address = {Genova, Italy}, author = {Artyomov, M.N. and Das, J. and Kardar, M. and Chakraborty, A.K.}, biburl = {https://www.bibsonomy.org/bibtex/2fc144ac1acbc94c7d7eff54344e7499b/statphys23}, booktitle = {Abstract Book of the XXIII IUPAP International Conference on Statistical Physics}, editor = {Pietronero, Luciano and Loreto, Vittorio and Zapperi, Stefano}, interhash = {8c06ba7bac80f623223b6ca16edbb6db}, intrahash = {fc144ac1acbc94c7d7eff54344e7499b}, keywords = {antagonism bifurcation gillespie monte-carlo scaling statphys23 stochastic t-cell topic-10}, month = {9-13 July}, timestamp = {2007-06-20T10:16:31.000+0200}, title = {Purely Stochastic Bifurcations in Cell Signalling}, url = {http://st23.statphys23.org/webservices/abstract/preview_pop.php?ID_PAPER=872}, year = 2007 }