QuestionQuestion

Part 1: In the following questions we will explore similarities between three gene sequences that vary significantly in their evolutionary distance from a common ancestor. The sequences that you will work with are given below:
• Human Gene
• Mouse Gene
• Yeast Gene
Devise a method to find the longest conserved substring shared by all three subsequences. Recall that a substring is a contiguous series of bases common to all three strings. Explain your approach. (You may write code to solve this part if you wish, however, if you do include both your code and your answer).
Part 2: Write a function to compute the minimal pairwise edit distance between two gene sequences such as the ones given part 1. Assume exact matches are weighted as +1, mismatches as 0, and any introduced gaps as -1
Longest Common Subsequence:
• A special case of edit distance where no substitutions are allowed
• A subsequence need not be contiguous, but order must be preserved Ex. If v = ATTGCTA then AGCA and TTTA are subsequences of v, but TGTT and ACGA are not
• The length of the LCS, s, is related to the strings edit distance, d, by:
d(u,w)=len(v)+len(w)–2s(u,w)
Difference between Gap and Mismatch
With two string GTAGGCTTA, GTAGATA
GTAGGCTTA
GTAGA - -TA
Here Red letters indicate mismatch while blue letters indicate gap. Total score for this pair using score of (1,0,-1) would be 6-1+0+0 = 5
Example: Consider these 4 sequences
       s1:    GATTCA
       s2:    GTCTGA
       s3:    GATATT
       s4:    GTCAGC
• with the scoring matrix: {Match = 1, Mismatch = -1, IntroGap = -1}
There are (4 Combination 2)= 6
• possible pairwise alignments
    s2: GTCTGA                         s1: GATTCA--
    s4: GTCAGC (score = 2)             s4: G-T-CAGC (score = 0)

    s1: GAT-TCA                         s2: G-TCTGA
    s2: G-TCTGA (score = 1)             s3: GATAT-T (score = -1)

    s1: GAT-TCA                         s3: GAT-ATT
    s3: GATAT-T (score = 1)            s4: G-TCAGC (score = -1)
• The best pairwise score, 2, is between s2 and s4

Part 3: Use the function that you wrote for Part 2 to find the edit distances(total score) between all pairs of genes sequences given in Part 1
editDistance (Human, Mouse) =
editDistance (Human, Yeast) =
editDistance (Mouse, Yeast) =

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from numpy import *

import sys
# Fix specifically because provided code hits a recursion limit in giant text files
sys.setrecursionlimit(10000)

# (SCORE_MATCH, SCORE_MISMATCH, SCORE_GAP)
# EDIT THIS TO MODIFY SCORE FORMULA; REST OF CODE WILL USE THIS!
SCORE_MATRIX = (0, 1, 1)

def findLCS(v, w):
    score = zeros((len(v)+1,len(w)+1), dtype="int32")
    backt = zeros((len(v)+1,len(w)+1), dtype="int32")
    for i in range(1,len(v)+1):
       for j in range(1,len(w)+1):
            # find best score at each vertex
            if (v[i-1] == w[j-1]):   
                score[i,j], backt[i,j] = max((score[i-1,j-1] + 1, 3),
                                             (score[i-1,j],1),
                                             (score[i,j-1],2))
            else:
                score[i,j], backt[i,j] = max((score[i-1,j],1),
                                             (score[i,j-1],2))
    return (score, backt)

def LCS(b,v...

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code.py, humanGene.seq, mouseGene.seq and yeastGene.seq.

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