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
