#!/usr/bin/env python
'''
A solution to a ROSALIND bioinformatics problem.
Problem Title: Maximum Matchings and RNA Secondary Structures
Rosalind ID: MMCH
Rosalind #: 040
URL: http://rosalind.info/problems/mmch/
'''
from math import factorial
from scripts import ReadFASTA
def nPr(n, k):
'''Returns the number of k-pernumatations of n.'''
return factorial(n)/factorial(n-k)
rna = ReadFASTA('data/rosalind_mmch.txt')[0][1]
# Counts the number of each times each nucleotide appears in the RNA string.
AU_num = [rna.count(nucleotide) for nucleotide in 'AU']
GC_num = [rna.count(nucleotide) for nucleotide in 'GC']
# There are nPr(max, min) edges for each AU, CG. Total number of edges is then the product.
max_matchings = nPr(max(AU_num), min(AU_num))*nPr(max(GC_num), min(GC_num))
print max_matchings
with open('output/040_MMCH.txt', 'w') as output_data:
output_data.write(str(max_matchings))
'''
A solution to a ROSALIND bioinformatics problem.
Problem Title: Maximum Matchings and RNA Secondary Structures
Rosalind ID: MMCH
Rosalind #: 040
URL: http://rosalind.info/problems/mmch/
'''
from math import factorial
from scripts import ReadFASTA
def nPr(n, k):
'''Returns the number of k-pernumatations of n.'''
return factorial(n) / factorial(n - k)
rna = ReadFASTA('data/rosalind_mmch.txt')[0][1]
# Counts the number of each times each nucleotide appears in the RNA string.
AU_num = [rna.count(nucleotide) for nucleotide in 'AU']
GC_num = [rna.count(nucleotide) for nucleotide in 'GC']
# There are nPr(max, min) edges for each AU, CG. Total number of edges is then the product.
max_matchings = nPr(max(AU_num), min(AU_num)) * nPr(max(GC_num), min(GC_num))
print max_matchings
with open('output/040_MMCH.txt', 'w') as output_data:
output_data.write(str(max_matchings))
#!/usr/bin/env python
'''
A solution to a ROSALIND bioinformatics problem.
Problem Title: Perfect Matchings and RNA Secondary Structures
Rosalind ID: PMCH
Rosalind #: 026
URL: http://rosalind.info/problems/pmch/
'''
from math import factorial
from scripts import ReadFASTA
rna = ReadFASTA('data/rosalind_pmch.txt')[0][1]
pmch = factorial(rna.count('A'))*factorial(rna.count('C'))
print pmch
with open('output/026_PMCH.txt', 'w') as output_data:
output_data.write(str(pmch))
