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Complex Adaptive Systems Modeling
Fig. 4 | Complex Adaptive Systems Modeling

Fig. 4

From: On the modeling and analysis of the biological regulatory network of NF-\({\kappa }\)B activation in HIV-1 infection

Fig. 4

The state graph of x and y genes; representing cyclic (homeostatic) and stable state (deadlock) behaviors of the system. The system evolves from silenced state (x,y) (0,0) leading towards (0,1) as in the absence of the inhibitor x, y is activated. Once the threshold value of 2 of y in the state (0, 2) is achieved (constant activation of y), it takes the system towards deadlock state (1, 2)

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