def iteration_RMS(Dna, k, t, iter):
bestMotifs = RandomizedMotifSearch(Dna, k, t)
for i in range(0, iter - 1):
motifs = RandomizedMotifSearch(Dna, k, t)
if score(motifs) < score(bestMotifs):
bestMotifs = motifs
return bestMotifs
def iteration_GS(Dna, k, t, N, iter):
bestMotifs = GibbsSampler(Dna, k, t, N)
for i in range(0, iter - 1):
motifs = GibbsSampler(Dna, k, t, N)
if score(motifs) < score(bestMotifs):
bestMotifs = motifs
return bestMotifs
def RandomizedMotifSearch(Dna, k, t):
'''
:param Dna: collection of strings
:param k: k-mer length
:param t: length of DNA
:return: t x k array of best motifs
'''
motifs = []
for seq in Dna.split("\n"):
rndIndex = rnd.randrange(0, len(seq) - k)
motifs.append(seq[rndIndex:rndIndex + k])
bestMotif = motifs
while True:
profile = constructProfile(motifs, k, t)
motifs = Motifs(Dna, k, profile)
if score(motifs) < score(bestMotif):
bestMotif = motifs
else:
return bestMotif
def GibbsSampler(Dna, k, t, N):
'''
:param Dna: collection of strings
:param k: k-mer length
:param t: length of DNA
:param N: number of runs
:return: t x k array of best motifs
'''
motifs = []
for seq in Dna.split("\n"):
rndIndex = random.randrange(0, len(seq) - k)
motifs.append(seq[rndIndex:rndIndex + k])
bestMotif = motifs
for i in range(0, N):
j = random.randrange(0, t)
gMotifs = [motif for index, motif in enumerate(motifs) if index != j]
profile = constructProfile(gMotifs, k, t)
motifs[j] = profile_random_probability_kmer(
Dna.split("\n")[j], k, profile)
if score(motifs) < score(bestMotif):
bestMotif = motifs
return bestMotif
profile = constructProfile(motifs, k, t)
motifs = Motifs(Dna, k, profile)
if score(motifs) < score(bestMotif):
bestMotif = motifs
else:
return bestMotif
def Motifs(Dna, k, profile):
motifs = []
for seq in Dna.split("\n"):
motifs.append(profileMostProbable(seq, k, profile))
return motifs
def iteration_RMS(Dna, k, t, iter):
bestMotifs = RandomizedMotifSearch(Dna, k, t)
for i in range(0, iter - 1):
motifs = RandomizedMotifSearch(Dna, k, t)
if score(motifs) < score(bestMotifs):
bestMotifs = motifs
return bestMotifs
if __name__ == "__main__":
bestMotifs = iteration_RMS(
"AGTCAACCCGGATCGCGGGTCGGTATGGCCACAGCACTCCGCGAACAGTCGGATAGGCAAGCACGGGGATCCGAACGCTCCAAGCGGCCATAAATTAGTTTCTTCTGGGTGCCATTAGAACTAGCCATCCTGCTAACCGCTCGGCGTAATGTGCACACTGCCTAAATTGCTTTAACGCATCCTATAAGTCAACCCGGATCG\nCGGGTCGGTATGGCCACAGCACTCCGCGAACAGTCGGATAGGCAAGCACGGGGATCCGAACGCTCCAAGCGGCCATATCGCTCCGGACCTCCAATTAGTTTCTTCTGGGTGCCATTAGAACTAGCCATCCTGCTAACCGCTCGGCGTAATGTGCACACTGCCTAAATTGCTTTAACGCATCCTATAAGTCAACCCGGATCG\nTGCGGGACTTGTAGATGGAATGCAGTTCTTGAGAGGTCCGTGCCTGGTTTTATCATTCCCGGGGAGCCCGATTGGGTGCCTGAGGCTTTCGGACTACAGGTTCCCCATAAACCACGAACCAATAGTAGCAGAAGCCAATAGCATCGAACTGGGCCCCCTTGCGAACGGACCTCCGCACGGGTGAGTATACTTCGGATACCC\nCGATATTGACACTGGTGACTCCCGCACCCTCATCGAGCGACCCCTGGGTTGCAGACATTAAGTTCTTGTTACACGTCATATTCATTTGGCTAAGGCTGCGGTAGTAAGCTACCCGGGACGATCTCAAAATCGAAAGTAACCTCCTTAGGGAAAACCTACTCACTCACCCACGGCCGTTCATCACTTTCGGACCATTCAGGT\nACTGTAGGCTTTTCAGGTTAAGACCACTACCCTTGGAAGCGCCAGGTGGGACCACCAATGAGATGATACATATGGGGCAGTTCTCTGGATGATTACACGCCACTCAGTCTAGCTTGTTTGCGCCAGTGAAAATTTGTCAACAAAGACGGCGATTGTAGGTCGAAACGGTAGTCCACTCGTGTTTCCATAAATGCCCTCGAA\nCATAGTTAGATCCACGTGCTGTTCCTAATAGAGACTTTACGCAATGCCGTATGGCTCTCTACGATGGGCTCAGGGGCATAGTTAAGTTACAAGTCAATTGAGATAGACTGGCGCAGACTTTGTGTCGAAACCTTCCTCCACTACGATGTTACCAACAGGGTTAGTGCAAGCATCCATCCATTATTTCACTCTGGCGGACTA\nAATGGCATGGTCCGCAGCCAAATATCGAGACACGAGTTGATACACCGTTCGATTAGCAACTCGAAAGTTACCTCCCTAGAGCGGCGTCGTCGGTTGATGTCATCTTTTCTCTGATCGCATTAATCTCGTGTAAAAAAATTAATGCATACTGAGGCACAGCTTCTTACAATCATGTGAGGTACTTCCGCCTGAATTCTGATG\nGCCTGTTGATAGGTCGGCTTTGTGTTGCCACTGCACAAGGAGGTAGCGTAGAGTGGCGTCACTTTCCAACTCGCGCTTTCAATGACCCCAACGTGCTGCAGATATGTGTAGAGTGAAATTACATAACGCCTTGCTATCCGTCCGTATAATTCCCAGTGGTTCGAAACGCTGCTCCAGGGATTAGGTGGCTAGCGAGGGCTT\nAAAGCTCTAAGATGTTCGCATGCGCAACGTGTAATTCAGGTACGCACGTCGAAACGGACCAAGTGACGATGGTTCACAACCGTTTGCCTAAGCGCGAGCAGTAACGTAAGCAAGTAGCGTGAACCAAGAGCATACCCTGTCTCTGGTTGAGACTATCGGCTTTGATAGAGCGTCTACAGTGCCACTCGTACATGTTCTCGA\nCAATAGCACTCGTTTTCCGATCGACCAGGACCTCCCCTTACCAGGCGGACTGTAATGAGCTGAACGGTTAAAAGGTCCAGTAGTAGCGTCGTGTCAATACCGGTCTTCTGACATCGGGGGAGGCCTGCGGAACAAAAAAAACAATATTATTTTGAATCGGGATCAGGGCACACACGAAATCATAGACACTACGTCTCGGCT\nGGTAGCATGCAAGACGGGGTCACCGTATGCAAGACAACTCACGTTAATAAAGGTCGAGCCAGCGGTTATAGGACACGAATTGAAGGTTTGTATAGACGGGCAAGCCTCATCCGTTGCCCATTGAGTCCCCTCGGGTCGACGAGGACCTCCTACACTGGATTTTTACCCAAGCCAAGACGAAAAACCTAGGCAAGTAACATT\nAGTTTTTGTATGCCTTTATTTGGGGGCGCAAAGGTTTGGATTTTAACTCAGGCGAGCTACGCCTACCGAAATTAAGCACCTGGTTAACGACGGGAAGAATATCTCACCTACAACTGACAAAGACCAGGCGCCACGTTCAGGTGACACGATTGGTAGGCGGTTCCTACCTTCCGATCGAAACGGACACACGATGTCTTGACA\nCCAGGCTGCTCCCAGTTATCGAGGCATCCTTGTGACTAGCGCCTCGAACGAGACCTCCTACCTATTGCTATATAAATCCAGCGTCGGATCTCACCCGAGACTCATCCCGTGCCTTCCCAGCCCTTGTTGGTCTAGTGCAGCTTAATTCTGTCGATAAAAGGGATGCTAGGTAAGTCATTCACGAATTTTCGTGTGTAGTAT\nACCTTGTAATATCTAATCGGCAGCTTCTCCAATACCATCGTCTCGGACCTCCAGTCGCTCGCTGCGTACGTACTCGTGTTCACACAGGGCGAACGCTGGCGGGCCGGGACGCTTCAGGGAGAGCGTTAGGCCATCAGCGTGACTCGGACGGTGACTATTGGATCTCACCCCCACTCAGGCGTCTCGGCACCCTCATAACCC\nCACTATCCTACCGTATCGGGCTCGAATATGCGCCATCCGAAGGGAGCGATTCAATAGGGACGGCCGGGTCGGCGCGCATATCTTGACTGCACGAAAATGAAACGGACCTCATATTCATGATCCACTGACTAGTAAATAGCTGCGAGGGCAGTTGTGGCAGGTCTTACAGGGTAAACGTTAACGAACTCCACTTTTCGTGGG\nTCACGCCCCTCGACGAAGTCGAAACGGAGACCCGTCCCACGCACATAGGAAGCCAGCGTCATCTGGCTTATGGGGCCGTAGGCTGGATGGTAGGCTCGACGTAGAGTGTCTCAATACAAGCTATTGGGCGCAGATTGATAAACCGCCCGCTTTTCAGACGTTAGTTACCTTCTGTGTGAGGATTGCAACATTACTTGCTAA\nACCCATCGCAGACCGAACTGGGGTTCTAGTACACGACGCCCACGCGATTTGTAGCGCACTTATTGGACTTGAGCCACTCAGCTCCCAGTCCATTCATATTTGTTACAATACGTCCCGTACCAGTGGAACCCCGTTTCCCCGACGGGCGTGCCCGGAGCATCTCGTAGAGGAAAAACGGACCTCCTGAAGGCGATTCGCCTG\nCTATATCCCTGGGTGCTTCACTCAGTCGAATGTGACCTCCAAGTAAAGAACCGGGATTACTTACCAACCTTAGCCGATAGCGATACTATAACGCTCCACCATCCTGACTGGCAACGCACCATTCCTCTTGCAACATGACGACCTGCCTTATTGGCCGATATTTAAGTCAAGAGACTCTGGTAAGTGCAGACGGTGTAAAAC\nGCTACGCCCGGGTGAGGAACGGGGTCCTCCACAGTTAACTATATTGCCAAATTCTTGGAGAAAGTCATAAACTTAAAATATCCATTGCAATACGAAGACCGTGGGGATGAACGCCGCGGGCTGTCTCTGTGTGGTGCTAAAACTCCCGGTGTAACCGATGCATGTTCTTTATCAGCACGGACCTCCCCATGATGCGCTCGC\nGGACATGATGGACTCAAGAGACTTCAGACGCCCTGGCCCCCGACTGCTTTTCTCGCCCGTGCGTAGCCCGCCGAAACGGACCTAAATAACCCCTTGACATACCAATGTACGATCTCGTCAATGTCCTTTTTACCCAACCCGATCAACAAGTCAGGGTCGAGCTACCGCCTGAAGTTGGCCACACACCGCAACCCAGACCGG",
15, 20, 1000)
print(listToString(bestMotifs).replace(" ", "\n"))
print(score(bestMotifs))