#互补序列获取
def complement(seq):
return seq.translate(str.maketrans('ACGTacgtRYMKrymkVBHDvbhd', 'TGCAtgcaYRKMyrkmBVDHbvdh'))
#DNA序列翻译
1 dna = "ATGCACGTGCGCTCACTGCGAGCTGCGGCGCCGCACAGCTTCGTGGCGCTCTGGGCACCCCTGTTCCTGCTGCGCTCCGCCCTGGCCGACTTCAGCCTGGACAACGAGGTGCACTCGAGCTTCATCCACCGGCGCCTCCGCAGCCAGGAGCGGCGGGAGATGCAGCGCGAGATCCTCTCCATTTTGGGCTTGCCCCACCGCCCGCGCCCGCACCTCCAGGGCAAGCACAACTCGGCACCCATGTTCATGCTGGACCTGTACAACGCCATGGCGGTGGAGGAGGGCGGCGGGCCCGGCGGCCAGGGCTTCTCCTACCCCTACAAGGCCGTCTTCAGTACCCAGGGCCCCCCTCTGGCCAGCCTGCAAGATAGCCATTTCCTCACCGACGCCGACATGGTCATGAGCTTCGTCAACCTCGTGGAACATGACAAGGAATTCTTCCACCCACGCTACCACCATCGAGAGTTCCGGTTTGATCTTTCCAAGATCCCAGAAGGGGAAGCTGTCACGGCAGCCGAATTCCGGATCTACAAGGACTACATCCGGGAACGCTTCGACAATGAGACGTTCCGGATCAGCGTTTATCAGGTGCTCCAGGAGCACTTGGGCAGGGAATCGGATCTCTTCCTGCTCGACAGCCGTACCCTCTGGGCCTCGGAGGAGGGCTGGCTGGTGTTTGACATCACAGCCACCAGCAACCACTGGGTGGTCAATCCGCGGCACAACCTGGGCCTGCAGCTCTCGGTGGAGACGCTGGATGGGCAGAGCATCAACCCCAAGTTGGCGGGCCTGATTGGGCGGCACGGGCCCCAGAACAAGCAGCCCTTCATGGTGGCTTTCTTCAAGGCCACGGAGGTCCACTTCCGCAGCATCCGGTCCACGGGGAGCAAACAGCGCAGCCAGAACCGCTCCAAGACGCCCAAGAACCAGGAAGCCCTGCGGATGGCCAACGTGGCAGAGAACAGCAGCAGCGACCAGAGGCAGGCCTGTAAGAAGCACGAGCTGTATGTCAGCTTCCGAGACCTGGGCTGGCAGGACTGGATCATCGCGCCTGAAGGCTACGCCGCCTACTACTGTGAGGGGGAGTGTGCCTTCCCTCTGAACTCCTACATGAACGCCACCAACCACGCCATCGTGCAGACGCTGGTCCACTTCATCAACCCGGAAACGGTGCCCAAGCCCTGCTGTGCGCCCACGCAGCTCAATGCCATCTCCGTCCTCTACTTCGATGACAGCTCCAACGTCATCCTGAAGAAATACAGAAACATGGTGGTCCGGGCCTGTGGCTGCCACTAG"
2
3 def trabslate_dna(sequence):
4 start_codon = 'ATG'
5 stop_codon = ('TAA', 'TAG', 'TGA' )
6 codontable = {
7 'ATA': 'I', 'ATC': 'I', 'ATT': 'I', 'ATG': 'M',
8 'ACA': 'T', 'ACC': 'T', 'ACG': 'T', 'ACT': 'T',
9 'AAC': 'N', 'AAT': 'N', 'AAA': 'K', 'AAG': 'K',
10 'AGC': 'S', 'AGT': 'S', 'AGA': 'R', 'AGG': 'R',
11 'CTA': 'L', 'CTC': 'L', 'CTG': 'L', 'CTT': 'L',
12 'CCA': 'P', 'CCC': 'P', 'CCG': 'P', 'CCT': 'P',
13 'CAC': 'H', 'CAT': 'H', 'CAA': 'Q', 'CAG': 'Q',
14 'CGA': 'R', 'CGC': 'R', 'CGG': 'R', 'CGT': 'R',
15 'GTA': 'V', 'GTC': 'V', 'GTG': 'V', 'GTT': 'V',
16 'GCA': 'A', 'GCC': 'A', 'GCG': 'A', 'GCT': 'A',
17 'GAC': 'D', 'GAT': 'D', 'GAA': 'E', 'GAG': 'E',
18 'GGA': 'G', 'GGC': 'G', 'GGG': 'G', 'GGT': 'G',
19 'TCA': 'S', 'TCC': 'S', 'TCG': 'S', 'TCT': 'S',
20 'TTC': 'F', 'TTT': 'F', 'TTA': 'L', 'TTG': 'L',
21 'TAC': 'Y', 'TAT': 'Y', 'TAA': '_', 'TAG': '_',
22 'TGC': 'C', 'TGT': 'C', 'TGA': '_', 'TGG': 'W'
23 }
24 start = sequence.find(start_codon)
25 codons = [] # Create a codon list to store codons generated from coding seq.
26 for i in range(start, len(sequence), 3):
27 if sequence[i:i+3] in stop_codons:
28 break
29 if sequence[i:i+3] in codontable.keys():
30 codons.append(sequence[i:i+3])
31 protein_sequence = ''.join([codontable[codon] for codon in codons]) #Translate condons to protein seq.
32 return "{0}_".format(protein_sequence)
33
34 protein_seq = translate_DNA(dna)
35 print(protein_seq)
#摘自https://www.cnblogs.com/nnufish/p/yuzhenpeng.html