Stochastic Model of Lambda Phage Infection (Lysis)
Description
Control of the outcome of phage lambda infection is one of the best understood regulatory systems. Thieffry and Thomas proposed a logical model to describe the dynamics of the network, which is a bistable switch between lysis and lysogeny. Lysis is the state where the phage will be replicated, killing the host. In other words, if the phage is in lysis, then CRO is active and other genes are repressed.
Variables
node1 = CI
node2 = CRO
node3 = CII
node4 = N
Transition Table and Functions
Click to see the transition table of lambda phage model
Click to see the functions of lambda phage model
Propensity Parameters
0.3 0.7
0.7 0.3
0.9 0.9
0.9 0.9
Initial State
0 0 0 0 (representing the state of the bacterium at the moment of phage infection)
Nodes of Interest
1, 2, 3, 4
Number of States
5
Number of Steps
50
Number of Simulations
100
Key Dynamic Features
Steady States
There is only 1 steady state in the system, which is 2 0 0 0.
Cell Population Simulation
Probability Distribution
Transition Matrix
Click to have the transition matrix of lambda phage model for Lysis
Other examples for Stochastic Discrete Dynamical Systems
Stochastic Model of Lambda Phage Infection (Lysogeny)
Stochastic Model of p53-Mdm2
References
D. Murrugarra, A. Veliz-Cuba, B. Aguilar, S. Arat, R. Laubenbacher "Modeling Stochasticity and Variability in Gene Regulatory Networks" (under review)
Author
Seda Arat
Last Updated
February 2012