coela

import re

class tRNAsynthetase(object):
    def __init__(self, filepath="/Users/coela/projects/ATS_interaction/data/uniprot/aatrnasy.txt"):
        fileHandle = open(filepath,'r')
        match_tRNA = re.compile("(\S+)-tRNA synthetases \((EC \S+)\)")
        count = 0
        switch = False
        self.info = dict()
        self.aadict = {"Alanyl" : "Ala",

coela

import sys
fileHandle = open(sys.argv[1],'r')
for line in fileHandle:
    line = line.rstrip()
    #print line
    lines = line.split("    ,")
    #print lines
    for i,ent in enumerate(lines):
        if i == 3:
            break

coela

import sys
from Bio import SeqIO
fh = open(sys.argv[1],"r") 
 
for gb_record in SeqIO.parse(fh, "genbank") :
  for (index, feature) in enumerate(gb_record.features) :
    if feature.type == 'source':
      print "\t".join([gb_record.name,feature.qualifiers['db_xref'][0].split(":")[1]])
      break

coela

from Bio import SeqIO
for seq_record in SeqIO.parse("NC_000913.gbk", "genbank"):
    for feature in seq_record.features:
        if feature.qualifiers.has_key('locus_tag'):
            start = feature.location.nofuzzy_start
            end = feature.location.nofuzzy_end
            print ">" + feature.qualifiers['locus_tag'][0]
            print seq_record.seq[start:end]

coela

from Bio import SeqIO
for seq_record in SeqIO.parse("NC_000913.gbk", "genbank"):
    print ">" + seq_record.id
    print seq_record.seq

coela

import glob
files = glob.glob('./*.gbff')
for file in files:
  fileHandle =  open( file , 'r' )
  for line in fileHandle:
    line = line.rstrip()
    print line

coela

from Bio import Entrez
import re
import sys

argvs = sys.argv

Entrez.email = "SN@example.com"
handle = Entrez.efetch(db="nucleotide", id=argvs[1],rettype="gb", retmode="text")
for line in handle.read().split("\n"):
    if re.match("  ORGANISM",line):

coela

###1

• process_name:preculture

• temperature: 32 celsius
• time : overnight
• comment : inoculating 30 ml of YES media
• input: yeast cell

• container: yeast agar plate

• input: yeast media
• output: precultured yeast

coela

#!/usr/bin/env python

import os 
import re 
import sys
argvs = sys.argv
if len(argvs) == 1:
    argvs.append("")
os.system('curl -k -X POST --data-urlencode \'payload={"channel": "#job", "username": "webhookbot", "text": "Your job is done: %s ", "icon_emoji": ":ghost:"}\' https://hooks.slack.com/services/hoge/hogehoge'%argvs[1])

coela

#-*- coding:utf-8 -*-
import sys
import numpy as np
from sklearn.ensemble import RandomForestClassifier
from sklearn.cross_validation import StratifiedKFold
from sklearn.grid_search import GridSearchCV
from sklearn.cross_validation import cross_val_score
from sklearn.datasets import make_blobs
from sklearn.ensemble import RandomForestClassifier
from sklearn.ensemble import ExtraTreesClassifier