#!/usr/bin/env python
from __future__ import print_function
import os
from prot import prepare_codon_table
from revp import read_fasta
from revc import reverse_complement
from rna import rna_transcription
from subs import substring_find
if __name__ == "__main__":
with open(os.path.join('data', 'rosalind_orf.txt')) as dataset:
seqs = read_fasta(dataset)
codon_table = prepare_codon_table(os.path.join('data', 'codon_table'))
output = []
dna = seqs.popitem()[1]
rna = (rna_transcription(dna), rna_transcription(reverse_complement(dna)))
for seq in rna:
for offset in (0, 1, 2):
for start_pos in substring_find(seq[offset:], 'AUG'):
current = []
for codon in (seq[i:i + 3]
for i in range(start_pos, len(seq), 3)):
if len(codon) == 3:
if codon_table[codon] == 'Stop' and current:
output.append(''.join(current))
current = []
def prepare_mass_table(filename):
table = prepare_codon_table(filename)
return {k: round(float(table[k]), 5) for k in table}
from __future__ import print_function
import os
from prot import prepare_codon_table
from revp import read_fasta
from revc import reverse_complement
from rna import rna_transcription
from subs import substring_find
if __name__ == "__main__":
with open(os.path.join("data", "rosalind_orf.txt")) as dataset:
seqs = read_fasta(dataset)
codon_table = prepare_codon_table(os.path.join("data", "codon_table"))
output = []
dna = seqs.popitem()[1]
rna = (rna_transcription(dna), rna_transcription(reverse_complement(dna)))
for seq in rna:
for offset in (0, 1, 2):
for start_pos in substring_find(seq[offset:], "AUG"):
current = []
for codon in (seq[i : i + 3] for i in range(start_pos, len(seq), 3)):
if len(codon) == 3:
if codon_table[codon] == "Stop" and current:
output.append("".join(current))
current = []
elif codon == "AUG" or current:
def prepare_mass_table(filename):
table = prepare_codon_table(filename)
return {k: round(float(table[k]), 5) for k in table}
#!/usr/bin/env python
from __future__ import print_function
import os
import operator
from functools import reduce
from prot import prepare_codon_table
if __name__ == "__main__":
with open(os.path.join('data', 'rosalind_mrna.txt')) as dataset:
protein_string = dataset.read().rstrip()
codon_table = prepare_codon_table(os.path.join('data', 'codon_table'))
stop_codons = [c for c in codon_table if codon_table[c] == 'Stop']
possibilities = []
for p in protein_string:
possibilities.append([(p, c) for c in codon_table
if codon_table[c] == p])
print((len(stop_codons) * reduce(operator.mul,
(len(p) for p in possibilities))) % 1000000)
