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The two probabilities were then plotted using MatLab. It is to be noted here that a 'random number generator' was used for plotting. The reason is, as the trigering of process will vary each time therefore 'random number generator' is a good choice.
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Revision as of 23:31, 28 October 2008






Let us consider the probability of CAI-1 interacting with our fusion kinase with a reaction rate k, diffusion rates D1 and D2 and they start at a distance d apart at the beginning of the time intervalThe reaction between two diffusing particles can be considered to take place in two steps. First the encounter of CAI-1 with Fusion kinase and second the actual reaction of passing protein to response regulatory receptor. If we let CAI-1 as entity A and fusion kinase as entity B then the rate of reaction can given as:

Where
is the probability of interaction between CAI-1 and Fusion Kinase.
is the reaction once CAI-1 has interacted with Fusion Kinase.
This interaction will follow the law of diffusion and if we let the process under consideration as Poisson process, the probability can be given as:


To find the probability of rest of reaction i.e. from activation of UvrY till the shining of our protein we can use the Gaussian Distribution, which can be given as:

The two probabilities were then plotted using MatLab. It is to be noted here that a 'random number generator' was used for plotting. The reason is, as the trigering of process will vary each time therefore 'random number generator' is a good choice.




The red curve is nearly half times wider than the green curve. It follows that standard deviation of red curve is greater thus the probability of contact (CAI-1 with Fusion kinase) is nearly half as compared to the probability of rest of reaction. To understand this consider an example of biscuits. Red curve shows each a biscuit made is different to the other produced under same conditions whereas green curve shows that the probability of two biscuits to be same is high.
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