class prosol:
"""interface of proso predictor"""
# initialize evironment
def __init__(self):
print("Initializing PROSOII script...")
self.n = 0
# set up the SequenceMaker
OrigSeq = '''MATKILALLALLALLVSATNAFIIPQCSLAPSASIPQFLPPVTSMGFEHPAVQAYRLQLALAASALQQPIAQLQQQSLAHLTLQTIATQQQQQQFLPSLSHLAVVNPVTYLQQQLLASNPLALANVAAYQQQQQLQQFMPVLSQLAMVNPAVYLQLLSSSPLAVGNAPTYLQQQLLQQIVPALTQLAVANPAAYLQQLLPFNQLAVSNSAAYLQQRQQLLNPLAVANPLVATFLQQQQQLLPYNQFSLMNPALQQPIVGGAIF'''
self.SequenceMaker = SequenceMaker(OrigSeq)
# initialize database interface
self.DbInterface = DbInterface('zeinsolub', 'prosol')
print("Initialized")
return
# Begin scrapping 5 sequences input for n times
# Unconstrained version
def start_unconstrained_upto(self, n, length):
print("Begin Mining...")
row = []
for i in range(n):
leng = random.randint(1, length)
randomSequence = self.SequenceMaker.generator_unconstrained(leng)
with open("./software/prosol/sequence.fasta", "w") as se:
se.write(">sample" + "\n")
se.write(randomSequence)
call([
"./software/prosol/multiple_prediction_wrapper_export.sh",
"sequence.fasta"
])
while not os.path.exists("seq_prediction.txt"):
time.sleep(.1)
with open("./software/prosol/seq_prediction.txt", "r") as rs:
for line in rs:
if line.startswith("SEQUENCE PREDICTIONS"):
nline = line.split(",")
solub = nline[3]
deter = True if solub > 0.45 else False
else:
raise ValueError
call(["rm", "seq_prediction.txt"])
aa_count_list, charge = self.SequenceMaker.count_aa_difference(
randomSequence)
row = [deter, solub, sum(aa_count_list), charge
] + aa_count_list + [randomSequence]
self.DbInterface.insert(row)
self.n += 1
print('---Written ' + str(self.n) + ' rows---')
return 0
def __init__(self):
print("Initializing PROSOII script...")
self.n = 0
# set up the SequenceMaker
OrigSeq = '''MATKILALLALLALLVSATNAFIIPQCSLAPSASIPQFLPPVTSMGFEHPAVQAYRLQLALAASALQQPIAQLQQQSLAHLTLQTIATQQQQQQFLPSLSHLAVVNPVTYLQQQLLASNPLALANVAAYQQQQQLQQFMPVLSQLAMVNPAVYLQLLSSSPLAVGNAPTYLQQQLLQQIVPALTQLAVANPAAYLQQLLPFNQLAVSNSAAYLQQRQQLLNPLAVANPLVATFLQQQQQLLPYNQFSLMNPALQQPIVGGAIF'''
self.SequenceMaker = SequenceMaker(OrigSeq)
# initialize database interface
self.DbInterface = DbInterface('zeinsolub', 'prosol')
print("Initialized")
return
def __init__(self):
print("Initializing PROSOII script...")
self.n = 0
# set up the SequenceMaker
OrigSeq = '''MATKILALLALLALLVSATNAFIIPQCSLAPSASIPQFLPPVTSMGFEHPAVQAYRLQLALAASALQQPIAQLQQQSLAHLTLQTIATQQQQQQFLPSLSHLAVVNPVTYLQQQLLASNPLALANVAAYQQQQQLQQFMPVLSQLAMVNPAVYLQLLSSSPLAVGNAPTYLQQQLLQQIVPALTQLAVANPAAYLQQLLPFNQLAVSNSAAYLQQRQQLLNPLAVANPLVATFLQQQQQLLPYNQFSLMNPALQQPIVGGAIF'''
self.SequenceMaker = SequenceMaker(OrigSeq)
# initialize driver and preload the website
chromedriver = '/Users/mac/webscript/chromedriver'
os.environ["webdriver.chrome.driver"] = chromedriver
self.driver = webdriver.Chrome(chromedriver)
self.url = 'http://mbiljj45.bio.med.uni-muenchen.de:8888/prosoII/prosoII.seam'
self.driver.get(self.url)
print("Opening Browser...")
# initialize database interface
self.DbInterface = DbInterface('zeinsolub',\
'proso')
print("Initialized")
def __init__(self):
print("Initializing PROSOII script...")
self.n = 0
# set up the SequenceMaker
OrigSeq = '''MATKILALLALLALLVSATNAFIIPQCSLAPSASIPQFLPPVTSMGFEHPAVQAYRLQLALAASALQQPIAQLQQQSLAHLTLQTIATQQQQQQFLPSLSHLAVVNPVTYLQQQLLASNPLALANVAAYQQQQQLQQFMPVLSQLAMVNPAVYLQLLSSSPLAVGNAPTYLQQQLLQQIVPALTQLAVANPAAYLQQLLPFNQLAVSNSAAYLQQRQQLLNPLAVANPLVATFLQQQQQLLPYNQFSLMNPALQQPIVGGAIF'''
self.SequenceMaker = SequenceMaker(OrigSeq)
# initialize database interface
self.DbInterface = DbInterface('zeinsolub', 'prosol')
conn = psycopg2.connect("dbname=zeinsolub")
cur = conn.cursor()
cur.execute("SELECT seq FROM proso2")
self.material = cur.fetchall()
cur.close()
conn.close()
self.index = 0
self.leng = len(self.material)
print("Initialized")
return
class prosoWeb:
"""interface of proso predictor"""
# initialize evironment
def __init__(self):
print("Initializing PROSOII script...")
self.n = 0
# set up the SequenceMaker
OrigSeq = '''MATKILALLALLALLVSATNAFIIPQCSLAPSASIPQFLPPVTSMGFEHPAVQAYRLQLALAASALQQPIAQLQQQSLAHLTLQTIATQQQQQQFLPSLSHLAVVNPVTYLQQQLLASNPLALANVAAYQQQQQLQQFMPVLSQLAMVNPAVYLQLLSSSPLAVGNAPTYLQQQLLQQIVPALTQLAVANPAAYLQQLLPFNQLAVSNSAAYLQQRQQLLNPLAVANPLVATFLQQQQQLLPYNQFSLMNPALQQPIVGGAIF'''
self.SequenceMaker = SequenceMaker(OrigSeq)
# initialize driver and preload the website
chromedriver = '/Users/mac/webscript/chromedriver'
os.environ["webdriver.chrome.driver"] = chromedriver
self.driver = webdriver.Chrome(chromedriver)
self.url = 'http://mbiljj45.bio.med.uni-muenchen.de:8888/prosoII/prosoII.seam'
self.driver.get(self.url)
print("Opening Browser...")
# initialize database interface
self.DbInterface = DbInterface('zeinsolub',\
'proso')
print("Initialized")
# Begin scrapping 50 sequences input for n times
# Unconstrained version
def start_unconstrained(self, \
n, length):
print("Begin Mining...")
for i in range(n):
# Initialize data buffer
data = []
# Enter 50 random sequence into textarea
for i in range(50):
leng = random.randint(1,\
length)
randomSequence = self.SequenceMaker.generator_unconstrained(
leng)
self.driver.find_element_by_id("form1:inText")\
.send_keys(">sample\n"+ randomSequence + "\n")
aa_count_list, charge = self.SequenceMaker.count_aa_difference(
randomSequence)
data.append([False, 0, sum(aa_count_list), charge] +
aa_count_list + [randomSequence])
# Submmit text via Ajax
self.driver.find_element_by_id("form1:j_id24").click()
# Wait for data table to be loaded
wait = WebDriverWait(self.driver, 100000)
element = wait.until(
EC.invisibility_of_element_located(
(By.ID, "_viewRoot:status.start")))
# Parsing raw HTML response and locate the result table
page_soup = soup(self.driver.page_source, "html.parser")
tb = page_soup.findAll(id="infoBlock_body")
slubs = tb[0].findAll("td")
# Prepare data buffer to be written to database
index = 0
for i in range(2, 3 * 50, 3):
temp = slubs[i].text.split(';')
data[index][0] = True if temp[0] == 'soluble' else False
data[index][1] = float(temp[1])
index += 1
# Upload data to database
for item in data:
self.DbInterface.insert(item)
self.n += 1
print('---Written ' + str(self.n) + ' rows---')
# Clear text area
self.driver.find_element_by_id("form1:inText").clear()
# close database session and return
self.DbInterface.close_connection()
return 0
# Begin scrapping 50 sequences input for n times with constrained charge
# Unconstrained version
def start_constrained(self, n, length, positive, negative):
print("Begin Mining...")
for i in range(n):
# Initialize data buffer
data = []
# Enter 50 random sequence into textarea
for i in range(50):
leng = length
charge = total_sub = -1
# make sure the sequence fits the reqirement
while not (charge >= (5 - negative) and charge <=
(5 + positive) and total_sub == length):
randomSequence = self.SequenceMaker.generator_constrained(
leng, -negative, positive)
aa_count_list, charge = self.SequenceMaker.count_aa_difference(
randomSequence)
total_sub = sum(aa_count_list)
# Input to text area
self.driver.find_element_by_id("form1:inText")\
.send_keys(">sample\n"+ randomSequence + "\n")
# write to buffer
data.append([False, 0, sum(aa_count_list), charge] +
aa_count_list + [randomSequence])
# Submmit text via Ajax
self.driver.find_element_by_id("form1:j_id24").click()
# Wait for data table to be loaded
wait = WebDriverWait(self.driver, 100000)
element = wait.until(
EC.invisibility_of_element_located(
(By.ID, "_viewRoot:status.start")))
# Parsing raw HTML response and locate the result table
page_soup = soup(self.driver.page_source, "html.parser")
tb = page_soup.findAll(id="infoBlock_body")
slubs = tb[0].findAll("td")
# Prepare data buffer to be written to database
index = 0
for i in range(2, 3 * 50, 3):
temp = slubs[i].text.split(';')
data[index][0] = True if temp[0] == 'soluble' else False
data[index][1] = float(temp[1])
index += 1
# Upload data to database
for item in data:
self.DbInterface.insert(item)
self.n += 1
print('---Written ' + str(self.n) + ' rows---')
# Clear text area
self.driver.find_element_by_id("form1:inText").clear()
# close database session and return
self.DbInterface.close_connection()
return 0
class prosol:
"""interface of proso predictor"""
# initialize evironment
def __init__(self):
print("Initializing PROSOII script...")
self.n = 0
# set up the SequenceMaker
OrigSeq = '''MATKILALLALLALLVSATNAFIIPQCSLAPSASIPQFLPPVTSMGFEHPAVQAYRLQLALAASALQQPIAQLQQQSLAHLTLQTIATQQQQQQFLPSLSHLAVVNPVTYLQQQLLASNPLALANVAAYQQQQQLQQFMPVLSQLAMVNPAVYLQLLSSSPLAVGNAPTYLQQQLLQQIVPALTQLAVANPAAYLQQLLPFNQLAVSNSAAYLQQRQQLLNPLAVANPLVATFLQQQQQLLPYNQFSLMNPALQQPIVGGAIF'''
self.SequenceMaker = SequenceMaker(OrigSeq)
# initialize database interface
self.DbInterface = DbInterface('zeinsolub', 'prosol')
conn = psycopg2.connect("dbname=zeinsolub")
cur = conn.cursor()
cur.execute("SELECT seq FROM proso2")
self.material = cur.fetchall()
cur.close()
conn.close()
self.index = 0
self.leng = len(self.material)
print("Initialized")
return
# Begin scrapping 5 sequences input for n times
# Unconstrained version
def recover(self):
print("Begin Recover...")
while self.index < self.leng:
row = []
buffer = []
sequenceBuffer = []
# for i in range(n):
with open("sequence.fasta", "w") as se:
for i in range(50):
randomSequence = self.material[self.index][0]
sequenceBuffer.append(randomSequence)
se.write(">sample" + str(i) + "\n")
se.write(randomSequence + "\n")
self.index += 1
print("------50 rows done------")
call(["./multiple_prediction_wrapper_export.sh", "sequence.fasta"])
while not os.path.exists("seq_prediction.txt"):
time.sleep(.1)
coun = 0
with open("seq_prediction.txt", "r") as rs:
for line in rs:
if line.startswith("SEQUENCE PREDICTIONS"):
nline = line.split(",")
solub = float(nline[3])
deter = True if solub > 0.45 else False
#print(solub, deter)
ranseq = sequenceBuffer[coun]
aa_count_list, charge = self.SequenceMaker.count_aa_difference(
ranseq)
row = [deter, solub,
sum(aa_count_list), charge
] + aa_count_list + [ranseq]
buffer.append(row)
coun += 1
call(["rm", "seq_prediction.txt"])
# print(coun)
for eachrow in buffer:
self.DbInterface.insert(eachrow)
self.n += 1
#print('---Written ' + str(self.n) + ' rows---')
return 0