Biopython으로 시퀀스 다뤄보기

전에요? 아니 그건 가져온거고. 

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시퀀스도 텍스트나 리스트처럼 인덱싱과 슬라이싱이 된다. 방법도 똑같다. 그래서 그건 생략할 예정임... 그리고 그거 아니어도 분량이 많아요 또. 

 

.count()

특정 문자열이 몇 개인지 세 준다. 뭐 시퀀스에서 아데닌이나 구아닌 갯수 세주고 그런거다. 이걸 이용하면 특정 단백질 시퀀스에서 특정 아미노산(카테고리면 겁나 세야된다...)이 차지하는 비율도 볼 수 있다. 

 

쉬어가는 코너-Primer에서 GC함량 구하기

아 이거 중요합니다. Primer 만들 때 중요한 요소 중 하나가 GC 함량이다. 참고로 여기서는 두 가지 방법으로 구해볼건데 첫번째는 .count()를 이용해 G와 C의 수를 세서 전체 DNA 염기 수로 나누는 거고, 두번째는 바이오파이썬의 모듈을 이용하는 방법이다. 

GC_cont=(primer.count('C')+primer.count('G'))/len(primer)
print(GC_cont*100,"%")

from Bio.SeqUtils import GC
primer=Seq('CAGCAAGCAAAGGTGTTCAA')
print(GC(primer),"%")

위는 직접 계산하는 방법이고 아래는 모듈을 사용했다. 모듈은 쓰려면 또 모셔와야 한다. 

 

시퀀스에 시퀀스를 더하면 1+1인가요 

시퀀스 그냥 +로 갖다 붙이거나 리스트업된 거 for문으로 붙이거나 join()쓰거나... 일단 for와 join 보고 갑시다. 

seq_list=[Seq('ATCC'),Seq('ATAT'),Seq('TNNN')]
add = Seq("")
for i in seq_list:
    add += i
print(add)

seq_list=[Seq('ATCC'),Seq('ATAT'),Seq('TNNN')]
spacer=Seq('N'*5)
print(spacer.join(seq_list))

 

돌연변이 만들기

시퀀스 데이터는 튜플마냥 안에 있는 내용물을 수정할 수 없다. 수정하려면 또 다른 모듈을 모셔와야 한다. 

from Bio.Seq import Seq
from Bio.Seq import MutableSeq #이걸 불러와서 
my_seq=Seq("GAATTC")
mutable_seq=MutableSeq(my_seq) #적용해줘야 한다
mutable_seq[0]="A"
print(mutable_seq)

Mutableseq에 던져둔 것은 타입도 

<class 'Bio.Seq.MutableSeq'>

로 바뀐다. 일반 시퀀스는 Seq. 

 

전사번역

입력한 시퀀스를 mRNA로 전사도 해 주고, 번역도 된다. 물론 다이렉트로 된다. 

 

from Bio import SeqIO
from Bio.Seq import Seq
from Bio.SeqUtils import GC
at5g40780=Seq('ATGGTAGCTCAAGCTCCTCATGATGATCATCAGGATGATGAGAAATTAGCAGCAGCGAGACAAAAAGAGATCGAAGATTGGTTACCAATTACTTCATCAAGAAATGCAAAGTGGTGGTACTCTGCTTTTCACAATGTCACCGCCATGGTCGGTGCCGGAGTTCTTGGACTCCCTTACGCCATGTCTCAGCTCGGATGGGGACCGGGAATTGCAGTGTTGGTTTTGTCATGGGTCATAACACTATACACATTATGGCAAATGGTGGAAATGCATGAAATGGTTCCTGGAAAGCGTTTTGATCGTTACCATGAGCTCGGACAACACGCGTTTGGAGAAAAACTCGGTCTTTATATCGTTGTGCCGCAACAATTGATCGTTGAAATCGGTGTTTGCATCGTTTATATGGTCACTGGAGGCAAATCTTTAAAGAAATTTCATGAGCTTGTTTGTGATGATTGTAAACCAATCAAGCTTACTTATTTCATCATGATCTTTGCTTCGGTTCACTTCGTCCTCTCTCATCTTCCTAATTTCAATTCCATCTCCGGCGTTTCTCTTGCTGCTGCCGTTATGTCTCTCAGCTACTCAACAATCGCATGGGCATCATCAGCAAGCAAAGGTGTTCAAGAAGACGTTCAATACGGTTACAAAGCGAAAACAACAGCCGGTACGGTTTTCAATTTCTTCAGCGGTTTAGGTGATGTGGCATTTGCTTACGCGGGTCATAATGTGGTCCTTGAGATCCAAGCAACTATCCCTTCAACGCCTGAGAAACCCTCAAAAGGTCCCATGTGGAGAGGAGTCATCGTTGCTTACATCGTCGTAGCGCTCTGTTATTTCCCCGTGGCTCTCGTTGGATACTACATTTTCGGGAACGGAGTCGAAGATAATATTCTCATGTCACTTAAGAAACCGGCGTGGTTAATCGCCACGGCGAACATCTTCGTCGTGATCCATGTCATTGGTAGTTACCAGATATATGCAATGCCGGTATTTGATATGATGGAGACTTTATTGGTCAAGAAGCTAAATTTCAGACCAACCACAACTCTTCGGTTCTTTGTCCGTAATTTCTACGTTGCTGCAACTATGTTTGTTGGTATGACGTTTCCGTTCTTCGGTGGGCTTTTGGCGTTCTTTGGTGGATTCGCGTTTGCCCCAACCACATACTTCCTCCCTTGCGTCATTTGGTTAGCCATCTACAAACCCAAGAAATACAGCTTGTCTTGGTGGGCCAACTGGGTATGCATCGTGTTTGGTCTTTTCTTGATGGTCCTATCGCCAATTGGAGGGCTAAGGACAATCGTTATTCAAGCAAAAGGATACAAGTTTTACTCATAA')
at5g40780_rc=at5g40780.reverse_complement()
# DNA와 상보적인 sequence를 만들었다.

at5g40780_mrna=at5g40780.transcribe()
at5g40780_mrna_rc=at5g40780_mrna.reverse_complement()
# 여기 RNA 추가요!
print(at5g40780_mrna)
AUGGUAGCUCAAGCUCCUCAUGAUGAUCAUCAGGAUGAUGAGAAAUUAGCAGCAGCGAGACAAAAAGAGAUCGAAGAUUGGUUACCAAUUACUUCAUCAAGAAAUGCAAAGUGGUGGUACUCUGCUUUUCACAAUGUCACCGCCAUGGUCGGUGCCGGAGUUCUUGGACUCCCUUACGCCAUGUCUCAGCUCGGAUGGGGACCGGGAAUUGCAGUGUUGGUUUUGUCAUGGGUCAUAACACUAUACACAUUAUGGCAAAUGGUGGAAAUGCAUGAAAUGGUUCCUGGAAAGCGUUUUGAUCGUUACCAUGAGCUCGGACAACACGCGUUUGGAGAAAAACUCGGUCUUUAUAUCGUUGUGCCGCAACAAUUGAUCGUUGAAAUCGGUGUUUGCAUCGUUUAUAUGGUCACUGGAGGCAAAUCUUUAAAGAAAUUUCAUGAGCUUGUUUGUGAUGAUUGUAAACCAAUCAAGCUUACUUAUUUCAUCAUGAUCUUUGCUUCGGUUCACUUCGUCCUCUCUCAUCUUCCUAAUUUCAAUUCCAUCUCCGGCGUUUCUCUUGCUGCUGCCGUUAUGUCUCUCAGCUACUCAACAAUCGCAUGGGCAUCAUCAGCAAGCAAAGGUGUUCAAGAAGACGUUCAAUACGGUUACAAAGCGAAAACAACAGCCGGUACGGUUUUCAAUUUCUUCAGCGGUUUAGGUGAUGUGGCAUUUGCUUACGCGGGUCAUAAUGUGGUCCUUGAGAUCCAAGCAACUAUCCCUUCAACGCCUGAGAAACCCUCAAAAGGUCCCAUGUGGAGAGGAGUCAUCGUUGCUUACAUCGUCGUAGCGCUCUGUUAUUUCCCCGUGGCUCUCGUUGGAUACUACAUUUUCGGGAACGGAGUCGAAGAUAAUAUUCUCAUGUCACUUAAGAAACCGGCGUGGUUAAUCGCCACGGCGAACAUCUUCGUCGUGAUCCAUGUCAUUGGUAGUUACCAGAUAUAUGCAAUGCCGGUAUUUGAUAUGAUGGAGACUUUAUUGGUCAAGAAGCUAAAUUUCAGACCAACCACAACUCUUCGGUUCUUUGUCCGUAAUUUCUACGUUGCUGCAACUAUGUUUGUUGGUAUGACGUUUCCGUUCUUCGGUGGGCUUUUGGCGUUCUUUGGUGGAUUCGCGUUUGCCCCAACCACAUACUUCCUCCCUUGCGUCAUUUGGUUAGCCAUCUACAAACCCAAGAAAUACAGCUUGUCUUGGUGGGCCAACUGGGUAUGCAUCGUGUUUGGUCUUUUCUUGAUGGUCCUAUCGCCAAUUGGAGGGCUAAGGACAAUCGUUAUUCAAGCAAAAGGAUACAAGUUUUACUCAUAA

.transcribe()를 이용하면 전사도 해 준다. 예시에 있는 시퀀스는 at5g40780(의 CDS). 

 

from Bio.Seq import Seq
at5g40780=Seq('ATGGTAGCTCAAGCTCCTCATGATGATCATCAGGATGATGAGAAATTAGCAGCAGCGAGACAAAAAGAGATCGAAGATTGGTTACCAATTACTTCATCAAGAAATGCAAAGTGGTGGTACTCTGCTTTTCACAATGTCACCGCCATGGTCGGTGCCGGAGTTCTTGGACTCCCTTACGCCATGTCTCAGCTCGGATGGGGACCGGGAATTGCAGTGTTGGTTTTGTCATGGGTCATAACACTATACACATTATGGCAAATGGTGGAAATGCATGAAATGGTTCCTGGAAAGCGTTTTGATCGTTACCATGAGCTCGGACAACACGCGTTTGGAGAAAAACTCGGTCTTTATATCGTTGTGCCGCAACAATTGATCGTTGAAATCGGTGTTTGCATCGTTTATATGGTCACTGGAGGCAAATCTTTAAAGAAATTTCATGAGCTTGTTTGTGATGATTGTAAACCAATCAAGCTTACTTATTTCATCATGATCTTTGCTTCGGTTCACTTCGTCCTCTCTCATCTTCCTAATTTCAATTCCATCTCCGGCGTTTCTCTTGCTGCTGCCGTTATGTCTCTCAGCTACTCAACAATCGCATGGGCATCATCAGCAAGCAAAGGTGTTCAAGAAGACGTTCAATACGGTTACAAAGCGAAAACAACAGCCGGTACGGTTTTCAATTTCTTCAGCGGTTTAGGTGATGTGGCATTTGCTTACGCGGGTCATAATGTGGTCCTTGAGATCCAAGCAACTATCCCTTCAACGCCTGAGAAACCCTCAAAAGGTCCCATGTGGAGAGGAGTCATCGTTGCTTACATCGTCGTAGCGCTCTGTTATTTCCCCGTGGCTCTCGTTGGATACTACATTTTCGGGAACGGAGTCGAAGATAATATTCTCATGTCACTTAAGAAACCGGCGTGGTTAATCGCCACGGCGAACATCTTCGTCGTGATCCATGTCATTGGTAGTTACCAGATATATGCAATGCCGGTATTTGATATGATGGAGACTTTATTGGTCAAGAAGCTAAATTTCAGACCAACCACAACTCTTCGGTTCTTTGTCCGTAATTTCTACGTTGCTGCAACTATGTTTGTTGGTATGACGTTTCCGTTCTTCGGTGGGCTTTTGGCGTTCTTTGGTGGATTCGCGTTTGCCCCAACCACATACTTCCTCCCTTGCGTCATTTGGTTAGCCATCTACAAACCCAAGAAATACAGCTTGTCTTGGTGGGCCAACTGGGTATGCATCGTGTTTGGTCTTTTCTTGATGGTCCTATCGCCAATTGGAGGGCTAAGGACAATCGTTATTCAAGCAAAAGGATACAAGTTTTACTCATAA')
# DNA sequence

at5g40780_mrna=at5g40780.transcribe()
# Transcription
print(at5g40780_mrna)
AUGGUAGCUCAAGCUCCUCAUGAUGAUCAUCAGGAUGAUGAGAAAUUAGCAGCAGCGAGACAAAAAGAGAUCGAAGAUUGGUUACCAAUUACUUCAUCAAGAAAUGCAAAGUGGUGGUACUCUGCUUUUCACAAUGUCACCGCCAUGGUCGGUGCCGGAGUUCUUGGACUCCCUUACGCCAUGUCUCAGCUCGGAUGGGGACCGGGAAUUGCAGUGUUGGUUUUGUCAUGGGUCAUAACACUAUACACAUUAUGGCAAAUGGUGGAAAUGCAUGAAAUGGUUCCUGGAAAGCGUUUUGAUCGUUACCAUGAGCUCGGACAACACGCGUUUGGAGAAAAACUCGGUCUUUAUAUCGUUGUGCCGCAACAAUUGAUCGUUGAAAUCGGUGUUUGCAUCGUUUAUAUGGUCACUGGAGGCAAAUCUUUAAAGAAAUUUCAUGAGCUUGUUUGUGAUGAUUGUAAACCAAUCAAGCUUACUUAUUUCAUCAUGAUCUUUGCUUCGGUUCACUUCGUCCUCUCUCAUCUUCCUAAUUUCAAUUCCAUCUCCGGCGUUUCUCUUGCUGCUGCCGUUAUGUCUCUCAGCUACUCAACAAUCGCAUGGGCAUCAUCAGCAAGCAAAGGUGUUCAAGAAGACGUUCAAUACGGUUACAAAGCGAAAACAACAGCCGGUACGGUUUUCAAUUUCUUCAGCGGUUUAGGUGAUGUGGCAUUUGCUUACGCGGGUCAUAAUGUGGUCCUUGAGAUCCAAGCAACUAUCCCUUCAACGCCUGAGAAACCCUCAAAAGGUCCCAUGUGGAGAGGAGUCAUCGUUGCUUACAUCGUCGUAGCGCUCUGUUAUUUCCCCGUGGCUCUCGUUGGAUACUACAUUUUCGGGAACGGAGUCGAAGAUAAUAUUCUCAUGUCACUUAAGAAACCGGCGUGGUUAAUCGCCACGGCGAACAUCUUCGUCGUGAUCCAUGUCAUUGGUAGUUACCAGAUAUAUGCAAUGCCGGUAUUUGAUAUGAUGGAGACUUUAUUGGUCAAGAAGCUAAAUUUCAGACCAACCACAACUCUUCGGUUCUUUGUCCGUAAUUUCUACGUUGCUGCAACUAUGUUUGUUGGUAUGACGUUUCCGUUCUUCGGUGGGCUUUUGGCGUUCUUUGGUGGAUUCGCGUUUGCCCCAACCACAUACUUCCUCCCUUGCGUCAUUUGGUUAGCCAUCUACAAACCCAAGAAAUACAGCUUGUCUUGGUGGGCCAACUGGGUAUGCAUCGUGUUUGGUCUUUUCUUGAUGGUCCUAUCGCCAAUUGGAGGGCUAAGGACAAUCGUUAUUCAAGCAAAAGGAUACAAGUUUUACUCAUAA

.translate()는 번역이다. (*은 종결코돈)

 

전사는 그냥 뭐 전사했구나 하고 넘어가도 되는데, 번역은 옵션이 좀 있으니 일단 보고 가자. 

to_stop=True: 처음 만나는 종결코돈에서 멈춘다

from Bio.Seq import Seq
at5g40780_mrna=Seq('AUGGUAGCUCAAGCUCCUCAUGAUGAUCAUCAGGAUGAUGAGAAAUUAGCAGCAGCGAGACAAAAAGAGAUCGAAGAUUGGUUACCAAUUACUUCAUCAAGAAAUGCAAAGUGGUGGUACUCUGCUUUUCACAAUGUCACCGCCAUGGUCGGUGCCGGAGUUCUUGGACUCCCUUACGCCAUGUCUCAGCUCGGAUGGGGACCGGGAAUUGCAGUGUUGGUUUUGUCAUGGGUCAUAACACUAUACACAUUAUGGCAAAUGGUGGAAAUGCAUGAAAUGGUUCCUGGAAAGCGUUUUGAUCGUUACCAUGAGCUCGGACAACACGCGUUUGGAGAAAAACUCGGUCUUUAUAUCGUUGUGCCGCAACAAUUGAUCGUUGAAAUCGGUGUUUGCAUCGUUUAUAUGGUCACUGGAGGCAAAUCUUUAAAGAAAUUUCAUGAGCUUGUUUGUGAUGAUUGUAAACCAAUCAAGCUUACUUAUUUCAUCAUGAUCUUUGCUUCGGUUCACUUCGUCCUCUCUCAUCUUCCUAAUUUCAAUUCCAUCUCCGGCGUUUCUCUUGCUGCUGCCGUUAUGUCUCUCAGCUACUCAACAAUCGCAUGGGCAUCAUCAGCAAGCAAAGGUGUUCAAGAAGACGUUCAAUACGGUUACAAAGCGAAAACAACAGCCGGUACGGUUUUCAAUUUCUUCAGCGGUUUAGGUGAUGUGGCAUUUGCUUACGCGGGUCAUAAUGUGGUCCUUGAGAUCCAAGCAACUAUCCCUUCAACGCCUGAGAAACCCUCAAAAGGUCCCAUGUGGAGAGGAGUCAUCGUUGCUUACAUCGUCGUAGCGCUCUGUUAUUUCCCCGUGGCUCUCGUUGGAUACUACAUUUUCGGGAACGGAGUCGAAGAUAAUAUUCUCAUGUCACUUAAGAAACCGGCGUGGUUAAUCGCCACGGCGAACAUCUUCGUCGUGAUCCAUGUCAUUGGUAGUUACCAGAUAUAUGCAAUGCCGGUAUUUGAUAUGAUGGAGACUUUAUUGGUCAAGAAGCUAAAUUUCAGACCAACCACAACUCUUCGGUUCUUUGUCCGUAAUUUCUACGUUGCUGCAACUAUGUUUGUUGGUAUGACGUUUCCGUUCUUCGGUGGGCUUUUGGCGUUCUUUGGUGGAUUCGCGUUUGCCCCAACCACAUACUUCCUCCCUUGCGUCAUUUGGUUAGCCAUCUACAAACCCAAGAAAUACAGCUUGUCUUGGUGGGCCAACUGGGUAUGCAUCGUGUUUGGUCUUUUCUUGAUGGUCCUAUCGCCAAUUGGAGGGCUAAGGACAAUCGUUAUUCAAGCAAAAGGAUACAAGUUUUACUCAUAA')
# 이건 mRNA 시퀀스고
at5g40780_protein=at5g40780_mrna.translate(to_stop=True)
#번역했다.
print(at5g40780_protein)
MVAQAPHDDHQDDEKLAAARQKEIEDWLPITSSRNAKWWYSAFHNVTAMVGAGVLGLPYAMSQLGWGPGIAVLVLSWVITLYTLWQMVEMHEMVPGKRFDRYHELGQHAFGEKLGLYIVVPQQLIVEIGVCIVYMVTGGKSLKKFHELVCDDCKPIKLTYFIMIFASVHFVLSHLPNFNSISGVSLAAAVMSLSYSTIAWASSASKGVQEDVQYGYKAKTTAGTVFNFFSGLGDVAFAYAGHNVVLEIQATIPSTPEKPSKGPMWRGVIVAYIVVALCYFPVALVGYYIFGNGVEDNILMSLKKPAWLIATANIFVVIHVIGSYQIYAMPVFDMMETLLVKKLNFRPTTTLRFFVRNFYVAATMFVGMTFPFFGGLLAFFGGFAFAPTTYFLPCVIWLAIYKPKKYSLSWWANWVCIVFGLFLMVLSPIGGLRTIVIQAKGYKFYS

table=2: 아래 사이트에서 제공하는 코돈 테이블로 번역할 수 있다. (기본은 1번 스탠다드)
https://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi

https://www.ncbi.nlm.nih.gov/Taxonomy/Utils/wprintgc.cgi

 

at5g40780_protein=at5g40780_mrna.translate(table=2)
MVAQAPHDDHQDDEKLAAA*QKEIEDWLPITSS*NAKWWYSAFHNVTAMVGAGVLGLPYAMSQLGWGPGIAVLVLSWVMTLYTLWQMVEMHEMVPGKRFDRYHELGQHAFGEKLGLYIVVPQQLIVEIGVCIVYMVTGGKSLKKFHELVCDDCKPIKLTYFIMIFASVHFVLSHLPNFNSISGVSLAAAVMSLSYSTIAWASSASKGVQEDVQYGYKAKTTAGTVFNFFSGLGDVAFAYAGHNVVLEIQATIPSTPEKPSKGPMW*GVIVAYIVVALCYFPVALVGYYIFGNGVEDNILMSLKKPAWLIATANIFVVIHVIGSYQMYAMPVFDMMETLLVKKLNF*PTTTLRFFVRNFYVAATMFVGMTFPFFGGLLAFFGGFAFAPTTYFLPCVIWLAIYKPKKYSLSWWANWVCIVFGLFLMVLSPIGGL*TIVIQAKGYKFYS*

위 CDS를 table 2(Vertebrate mitochondria)로 설정하고 번역한 결과. *은 종결 코돈이다. 

stop_symbol="@": 종결코돈의 기호를 @로 바꾼다. 

at5g40780_protein=at5g40780_mrna.translate(table=2,stop_symbol="-")
MVAQAPHDDHQDDEKLAAA-QKEIEDWLPITSS-NAKWWYSAFHNVTAMVGAGVLGLPYAMSQLGWGPGIAVLVLSWVMTLYTLWQMVEMHEMVPGKRFDRYHELGQHAFGEKLGLYIVVPQQLIVEIGVCIVYMVTGGKSLKKFHELVCDDCKPIKLTYFIMIFASVHFVLSHLPNFNSISGVSLAAAVMSLSYSTIAWASSASKGVQEDVQYGYKAKTTAGTVFNFFSGLGDVAFAYAGHNVVLEIQATIPSTPEKPSKGPMW-GVIVAYIVVALCYFPVALVGYYIFGNGVEDNILMSLKKPAWLIATANIFVVIHVIGSYQMYAMPVFDMMETLLVKKLNF-PTTTLRFFVRNFYVAATMFVGMTFPFFGGLLAFFGGFAFAPTTYFLPCVIWLAIYKPKKYSLSWWANWVCIVFGLFLMVLSPIGGL-TIVIQAKGYKFYS-

위 예시에서는 -로 바꿨다. 

 

글자 다이렉트로 전사번역하기

시퀀스도 글자긴 한데 str과 다른 점이 있다면 상보적인 시퀀스를 만들 수 있다는 것이다. 근데 그렇다고 헐 시퀀스 안만들었다! 망했다! 이건 아니고... 

from Bio.Seq import reverse_complement, transcribe, back_transcribe, translate #질문있는데 이걸 꼭 이렇게 불러야겠니
insulin="GCATTCTGAGGCATTCTCTAACAGGTTCTCGACCCTCCGCCATGGCCCCGTGGATGCATCTCCTCACCGTGCTGGCCCTGCTGGCCCTCTGGGGACCCAACTCTGTTCAGGCCTATTCCAGCCAGCACCTGTGCGGCTCCAACCTAGTGGAGGCACTGTACATGACATGTGGACGGAGTGGCTTCTATAGACCCCACGACCGCCGAGAGCTGGAGGACCTCCAGGTGGAGCAGGCAGAACTGGGTCTGGAGGCAGGCGGCCTGCAGCCTTCGGCCCTGGAGATGATTCTGCAGAAGCGCGGCATTGTGGATCAGTGCTGTAATAACATTTGCACATTTAACCAGCTGCAGAACTACTGCAATGTCCCTTAGACACCTGCCTTGGGCCTGGCCTGCTGCTCTGCCCTGGCAACCAATAAACCCCTTGAATGAG"
#Wrap 알아서 켜주면 안되냐고...
insulin_rc=reverse_complement(insulin)
insulin_mrna=transcribe(insulin)
insulin_prot=translate(insulin)
# 순서대로 reverse complement/전사/번역 
print(insulin_rc)
print(insulin_mrna)
print(insulin_prot)

시퀀스때랑 불러오는 건 다르지만 어쨌든 된다. 

 

코돈 테이블 보기

내 블로그 아미노산 배경화면에도 있긴 한데 그걸 누가 외웁니까... 아무튼 그렇다. 

 

from Bio.Data import CodonTable
standard_table = CodonTable.unambiguous_dna_by_name["Standard"]
print(standard_table)

from Bio.Data import CodonTable
standard_table = CodonTable.unambiguous_dna_by_id[1]
print(standard_table)

둘 다 같은 테이블을 호출하는건데, 위에껀 이름으로 부르고 밑에껀 ID로 부른다. 이름이나 ID는 위에 올린 NCBI 주소로 가면 나오니까 그걸로 부르면 된다. 

 

Table 1 Standard, SGC0

  |  T      |  C      |  A      |  G      |
--+---------+---------+---------+---------+--
T | TTT F   | TCT S   | TAT Y   | TGT C   | T
T | TTC F   | TCC S   | TAC Y   | TGC C   | C
T | TTA L   | TCA S   | TAA Stop| TGA Stop| A
T | TTG L(s)| TCG S   | TAG Stop| TGG W   | G
--+---------+---------+---------+---------+--
C | CTT L   | CCT P   | CAT H   | CGT R   | T
C | CTC L   | CCC P   | CAC H   | CGC R   | C
C | CTA L   | CCA P   | CAA Q   | CGA R   | A
C | CTG L(s)| CCG P   | CAG Q   | CGG R   | G
--+---------+---------+---------+---------+--
A | ATT I   | ACT T   | AAT N   | AGT S   | T
A | ATC I   | ACC T   | AAC N   | AGC S   | C
A | ATA I   | ACA T   | AAA K   | AGA R   | A
A | ATG M(s)| ACG T   | AAG K   | AGG R   | G
--+---------+---------+---------+---------+--
G | GTT V   | GCT A   | GAT D   | GGT G   | T
G | GTC V   | GCC A   | GAC D   | GGC G   | C
G | GTA V   | GCA A   | GAA E   | GGA G   | A
G | GTG V   | GCG A   | GAG E   | GGG G   | G
--+---------+---------+---------+---------+--

아무튼 소환했다. 

 

색인

저거 검색도 된다. 실화다. 

 

print(standard_table.stop_codons)
['TAA', 'TAG', 'TGA']

해당 테이블의 Stop codon을 검색하거나 

 

print(mito_table.start_codons)
['ATT', 'ATC', 'ATA', 'ATG', 'GTG']

개시코돈을 검색하거나(저거 2번 테이블이다)

 

print(standard_table.forward_table['AAA'])
K

특정 코돈이 지정하는 아미노산을 찾을 수 있다.