def greedyMotifSearch(dna, k, t):
best_motifs = []
for string in dna:
best_motifs.append(string[0:k])
for i in range(len(dna[0]) - k + 1):
motifs = [dna[0][i:i + k]]
for j in range(1, t):
profile_matrix = formProfile(motifs)
motifs.append(detectMostProbableKMer(dna[j], k, profile_matrix))
if score(motifs) < score(best_motifs):
best_motifs = motifs
return best_motifs
def gibbsSampler(dna, k, t, N):
motifs = []
n = len(dna[0])
for i in xrange(t):
index = random.randint(0, n - k)
motifs.append(dna[i][index:index + k])
best_motifs = motifs
for j in xrange(N):
r = random.randint(0, t - 1)
profile_matrix = formProfileGibbs(motifs, r)
motif = detectMostProbableKMer(dna[r], k, profile_matrix)
motifs = [motif if index == r else m for index, m
in enumerate(motifs)]
if score(motifs) < score(best_motifs):
best_motifs = motifs
return best_motifs
def selectMotifs(profile_matrix, dna, k):
motifs = []
for string in dna:
motifs.append(detectMostProbableKMer(string, k, profile_matrix))
return motifs
