Code Challenge: Implement GibbsSampler$().$

$-$ Input: Integers $\backslash ($ k$,$ t $\backslash ),$ and $\backslash ($ N $\backslash ),$ followed by a space$-$separated collection of strings Dna.

$-$ Output: The strings BestMotifs resulting from running GibbsSampler $($Dna$,$ k$,\backslash ($ t$,$ N $\backslash ))$ with $1000$ random starts. Remember to use pseudocounts!

Currently supported languages are: Python, C$++,$ Java, Go$.$ We would love to add more languages in the future! For now, to get credit for the problem, you will need to code in one of the supported languages. If you want to solve this problem in another language and are not interested in receiving points, then please check out the ungraded "Rosalind$-$style" problem at the end of this chapter.

Debug Datasets

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Sample Input:

$85100$

CGCCCCTCTCGGGGGTGTTCAGTAAACGGCCA GGGCGAGGTATGTGTAAGTGCCAAGGTGCCAG TAGTACCGAGACCGAAAGAAGTATACAGGCGT

TAGATCAAGTTTCAGGTGCACGTCGGTGAACC AATCCACCAGCTCCACGTGCAATGTTGGCCTA

Sample Output:

AACGGCCA AAGTGCCA TAGTACCG AAGTTTCA ACGTGCAA $```$

import sys

# Please do not remove package declarations because these are used by the autograder.

# Insert your gibbs$\_$sampler function here, along with any subroutines you need

def gibbs$\_$sampler$($dna: list$[$str$],$ k: int, t: int, n: int$)->$ list$[$str$]$:

$"""$Implements the GibbsSampling algorithm for notif finding."""

pass

$```$