Part 2: Stochastic model of the -phage lysis/lysogeny decision network. The same fundamental model can be implemented as a stochastic model by use of the Gillespie algorithm. We use the same equations to define the fundamental rates of each reaction CTOprot v4 = Xcl.rnalclrna] prot VS = Werolcrorna] 6Xero,prot CTOprot 8Xcro,rna CTOPna c,1/2 where the concentrations correspond the the numbers of molecules present. The algorithm can be generally outlined as: for each step find time increment choose next reaction increment or decrement molecule numbers by 1, as appropriate for the chosen reaction The time increment is chosen from an exponential distribution with coefficient Rtot, where Rtot is the total of all reaction rates (Rtot - proportional to Vi (PG) = . 1. Implement this stochastic model in MATLAB, using the same constants as for the deterministic model. Beginning with all concentrations equal to zero, run a simulation for 50,000 steps, and plotting all concentrations versus time. Discuss what you observe Part 2: Stochastic model of the -phage lysis/lysogeny decision network. The same fundamental model can be implemented as a stochastic model by use of the Gillespie algorithm. We use the same equations to define the fundamental rates of each reaction CTOprot v4 = Xcl.rnalclrna] prot VS = Werolcrorna] 6Xero,prot CTOprot 8Xcro,rna CTOPna c,1/2 where the concentrations correspond the the numbers of molecules present. The algorithm can be generally outlined as: for each step find time increment choose next reaction increment or decrement molecule numbers by 1, as appropriate for the chosen reaction The time increment is chosen from an exponential distribution with coefficient Rtot, where Rtot is the total of all reaction rates (Rtot - proportional to Vi (PG) = . 1. Implement this stochastic model in MATLAB, using the same constants as for the deterministic model. Beginning with all concentrations equal to zero, run a simulation for 50,000 steps, and plotting all concentrations versus time. Discuss what you observe