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Fig. 3 | BMC Systems Biology

Fig. 3

From: Simulating heterogeneous populations using Boolean models

Fig. 3

Simulation of a heterogeneous population of T-cell networks. a Boolean model of a T-cell activation, introduced in [27]. Model variables correspond to blue nodes; red nodes are introduced to describe loss-of-function alterations of the network. Model variables used in the example equations in the text are given boldface letters corresponding to their subscripts. b Time evolution of one individual modeled by the T-cell network, starting from a random initial state. White/black rectangles signify OFF/ON Boolean states. c Time evolution of the population fraction having activated CRE elements and/or expressing the transcription factor AP1 in a heterogeneous population of T-cell networks, computed using a product basis calculation. The heterogeneous population begins at t=0 as a uniform mixture of all possible 233≈1010 initial states of the upstream portion of the model. d The effect of a 10−4 knock-out mutation rate per gene in the heterogeneous population. Monte Carlo, but not the product basis calculation, required this high rate of mutations in order to detect persistent coactivation of CRE and AP1. e The co-occurrence of CRE activation and AP1 expression in mutated networks shown on a log10 scale (dotted red line), compared with the amount of this coexpression coincident with mutated cCbl (purple dots). The mutated fraction was computed by subtracting the time series of CRE AP1 WT-cCbl from the time series of CRE AP1

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