In this project, we will look for buried treasure, in the form of a 9-char motif, in the following three sequences: A: CCAGACATTGTCCTAAGTCTAGAGACTAGCAAAAAGTGCGGGGAGGTGGGGGTATTT CCTCCCGACCACAATGAACATACGGAGACGGTCTGGGACCTTA B: GGCGGTGGTGGCAATCTCAGGGACCCCGACATAGTCACCAGGCCTTGTTCCGGATGT CACGCACGACTAGACCAACCTAAATTCACATGTCCTGCCTTCA C: AATTGACGAAGCTGAGCCCAGAGTGCTATGTCCTGAACCGTTAATGCCGACTTTGTC TTGTTAACTTTAACGTCAGGAAAATGACTCCTACGGAGCGGAA Each of the sequences is exactly 100 nucleotides long. Using Python, implement the motif finder described in Lecture 3 to identify the highest scoring motif in this collection. Report the motif and score. "Reporting the motif means the 9-letter extracts from A, B and C. HINT: Consider this a one-time problem - i.e. do not make your program in any way 'general'. Hardwire it to handle exactly three sequences, in fact feel free to hard code the sequences into your program. Importantly, start by writing a function (call it 'score') that computes the profile score for any given starting positions in the three sequences. Since you need to extract the three aligned rows of the motif to compute that score, your function might as well return those too (i.e. return score AND motif). Do you notice anything interesting about the motif you discover? In this project, we will look for buried treasure, in the form of a 9-char motif, in the following three sequences: A: CCAGACATTGTCCTAAGTCTAGAGACTAGCAAAAAGTGCGGGGAGGTGGGGGTATTT CCTCCCGACCACAATGAACATACGGAGACGGTCTGGGACCTTA B: GGCGGTGGTGGCAATCTCAGGGACCCCGACATAGTCACCAGGCCTTGTTCCGGATGT CACGCACGACTAGACCAACCTAAATTCACATGTCCTGCCTTCA C: AATTGACGAAGCTGAGCCCAGAGTGCTATGTCCTGAACCGTTAATGCCGACTTTGTC TTGTTAACTTTAACGTCAGGAAAATGACTCCTACGGAGCGGAA Each of the sequences is exactly 100 nucleotides long. Using Python, implement the motif finder described in Lecture 3 to identify the highest scoring motif in this collection. Report the motif and score. "Reporting the motif means the 9-letter extracts from A, B and C. HINT: Consider this a one-time problem - i.e. do not make your program in any way 'general'. Hardwire it to handle exactly three sequences, in fact feel free to hard code the sequences into your program. Importantly, start by writing a function (call it 'score') that computes the profile score for any given starting positions in the three sequences. Since you need to extract the three aligned rows of the motif to compute that score, your function might as well return those too (i.e. return score AND motif). Do you notice anything interesting about the motif you discover