def main1():
input_dna = '''ttACCTtaac
gATGTctgtc
ccgGCGTtag
cactaACGAg
cgtcagAGGT'''
dna = [Seq(line.strip(), IUPAC.unambiguous_dna) for line in input_dna.upper().split('\n')]
input_motifs = '''ttac
gtct
ggcg
taac
gtca'''
motifs = [Seq(line.strip(), IUPAC.unambiguous_dna) for line in input_motifs.upper().split('\n')]
print_motifs(motifs)
profile = make_profile(motifs, 4)
print
print profile
print
new_motifs = []
for seq in dna:
new_motifs.append(profile_most_prob(profile, seq, 4))
print_motifs(new_motifs)
profile = make_profile(new_motifs, 4)
print
print profile
print
new_motifs = []
for seq in dna:
new_motifs.append(profile_most_prob(profile, seq, 4))
print_motifs(new_motifs)
def randomized_motif_search(dna, k, t):
best_motifs = []
for seq in dna:
pos = random.randrange(len(seq) - k + 1)
best_motifs.append(seq[pos:pos + k])
while True:
profile = make_profile(best_motifs, k)
motifs = [profile_most_prob(profile, seq, k) for seq in dna]
if score_motifs(motifs) < score_motifs(best_motifs):
best_motifs = motifs
else:
return best_motifs
def run():
best_motifs = []
for seq in dna:
pos = random.randrange(len(seq) - k + 1)
best_motifs.append(seq[pos:pos + k])
best_score = score_motifs(best_motifs)
motifs = best_motifs[:]
for _ in range(N):
i = random.randrange(t)
profile = make_profile(motifs[:i] + motifs[i + 1:], k)
motifs[i] = profile_rand_kmer(profile, dna[i], k)
score = score_motifs(motifs)
if score < best_score:
best_motifs, best_score = motifs[:], score
print_motifs(best_motifs)
return best_score, best_motifs
