Optimal code similar to real code: First try

First, I generate 10^6 random codes, and choose the best one (alternatively, I could use one of the ‘optimal codes’ in the papers):

>> [codigo_opt,MS0_opt,MS_bases_opt,MS0,MS_bases]=optimizacodigo(codigo,10^6,1);
>> hist(MS0,100)

>> MS0_opt
MS0_opt =
4.4522
>> muestracodigo_fig(codigo_opt)

>> muestracodigo_fig(codigo)

>> save codigo_opt
>> [errormedio,matriz]=comparacodigos(codigo,codigo_opt);
>> errormedio
errormedio =
0.9531

Very different, as expected.

I find the code equivalent to the optimal one, most similar to the real genetic code:

>> [codigo_final,errormin,errormedio]=acercacodigos(codigo,codigo_opt);
>> errormin
errormin =
0.7656
>> errormin*64
ans =
49
>> muestracodigo_fig(codigo_final)

Not very-very similar. Only 15 (64-49) codons match.

Now I represent again the real and the most similar optimal codes, but colours represent polar requirement:

>> muestracodigo_fig(codigo,1)
>> figure
>> muestracodigo_fig(codigo_final,1)

One Response to “Optimal code similar to real code: First try”

  1. gonzalopolavieja Says:

    What if you look not to the most simlar among the equivalent optimal codes, but the one with closet polarity.

    Also I wonder whether just choosing tehe (numerical) optimal is too retrictive. We should take a little group of the most optimal ones.


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