Calculate A's Evolution Over 1000 Generations with Mutation Probability

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Homework Help Overview

The problem involves calculating the evolution of a strand of length L that starts as all A's over 1000 generations, considering a mutation probability μ for each letter to change to C, G, or T. The task is to express the number of A's as a function of μ and relate it to the expected number of A's, denoted as N_A.

Discussion Character

  • Exploratory, Assumption checking, Conceptual clarification

Approaches and Questions Raised

  • Participants discuss the initial approach of calculating the number of A's by successively applying the mutation probability. There is a focus on understanding the correct application of mutation versus non-mutation probabilities. Questions arise about the implications of these probabilities on the expected number of A's over generations.

Discussion Status

Some participants have provided guidance on correcting the approach to focus on the probability of not mutating. There is acknowledgment of confusion regarding the calculations, and clarification is being sought on how to express the number of A's correctly across generations.

Contextual Notes

Participants are working under the assumption that once a letter mutates, it cannot mutate again, and there is a need to clarify the implications of the mutation probability on the expected outcomes over multiple generations.

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Homework Statement


A strand of length L begins life as all A's. Assume that each letter evolves independent of all the rest until today, 1000 generations later. Within each generation there is a ##\mu## probability that the letter mutates to either C, G, T. Finally, assume that once a letter mutates that it cannot mutate again.
Calculate the number of A's as a function of ##\mu##. Then equate this expectation to ##N_A## and write down a function for ##\mu## in terms of##N_A##.

Homework Equations

The Attempt at a Solution


So, I have 1000 generations where each A has the possibility to mutate to something else with probability ##\mu##. The first generation the total number of A's is ##N_A=L##. The second generation we must multiply each A by the mutation probability. Since there is L A's we will get: ##N_A=\mu L##. The third generation occurs and we have to multiply the current number of A's by ##\mu## again. Which gives us ##N_A=\mu \mu L##. Taking this to 1000 generations we'd have ##N_A= \mu^{1000-1} L## which doesn't really seem likely at all.

Any suggestions, or is this correct?
 
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What your solution is working toward is the number of non-A's in a given generation. What you want is to apply the opposite probability, the probability of not mutating.

For example, think if the probability was 1% to mutate. After the 1st generation, you would expect .99L A genes and .01L non-A genes. if you just took NA = μL, you would effectively be saying that NA in the first generation is (.01)L which would actually be the Nnot-A

So, your concept of multiplying the probability successively is correct, but you just need to use the right probability.
 
Last edited:
You are right. I had a feeling that I was getting the opposite result that I was meaning to get. I should have realized I had them mixed up! Thanks!
 
No problem!

And one more thing, if the second generation is P2L, and the third is P3L. Wouldn't the 1000th be P1000L? Just wondering since you put P1000-1L
(assuming P is the corrected probability)

Edit: nevermind, the first generation is just L, haha :oops:
 

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