def protein_query(protname):
protein_to_search = tfc_label = ''
query = createquery('SELECT ?subject WHERE {?subject sybig:name "' +
str(protname) + '"}')
# print("Checking where " + protname + "belongs to")
uri_unparsed = rq.get(FUSEKI_URL,
params={
'format': 'json',
'query': query
})
uri = uri_unparsed.json()
for x in uri['results']['bindings']:
protein_to_search = x['subject']['value']
# print("Found " + protein_to_search)
query = createquery('SELECT ?subject WHERE {<' +
str(protein_to_search) +
'> sybig:belongs_to ?subject}')
tfc_unparsed = rq.get(FUSEKI_URL,
params={
'format': 'json',
'query': query
})
tfc = tfc_unparsed.json()
for y in tfc['results']['bindings']:
tfc_label = tfc_uri_to_label(y['subject']['value'])
return protein_to_search, tfc_label
def collect_tfc_ids(mode, level):
tf_list = []
if level == "All":
query = createquery(
'SELECT ?subject WHERE {?subject sybig:tfclass_id ?o}')
else:
query = createquery(
'SELECT ?subject WHERE {?subject sybig:tfclass_id ?o ; sybig:level "'
+ str(level) + '" .}')
tf_list_unparsed = rq.get(FUSEKI_URL,
params={
'format': 'json',
'query': query
})
tf_list_json = tf_list_unparsed.json()
for x in tf_list_json['results']['bindings']:
if mode == 0:
element = x['subject']['value'] # .replace("localhost", "coyote")
tf_list.append(element)
else:
temp_ids = x['subject']['value']
id_splitter = temp_ids.split('/')
id_splitter = id_splitter[len(id_splitter) - 1]
tf_list.append(id_splitter)
tf_list.sort()
return tf_list
def get_node(tfc_id):
query = createquery('SELECT ?subject ?pred ?object WHERE {\n' +
'?subject sybig:tfclass_id "' + tfc_id + '" .\n' +
'?subject ?pred ?object}\n')
res = rq.get(FUSEKI_URL, params={'format': 'json', 'query': query})
data = res.json()
# Return the URI to given TFClass ID aswell
tmp = data['results']['bindings'][0]
subject = tmp['subject']['value']
return data, subject
def collect_tf_proteins():
prot_list = []
query = createquery(
'SELECT ?subject WHERE { ?subject sybig:level ?o FILTER ('
' !EXISTS { ?subject sybig:tfclass_id ?o2})}')
prot_list_unparsed = rq.get(FUSEKI_URL,
params={
'format': 'json',
'query': query
})
prot_list_json = prot_list_unparsed.json()
for x in prot_list_json['results']['bindings']:
prot_list.append(x['subject']['value'])
prot_list.sort()
return prot_list
def add_single_dbd(dbd):
dbd = dbd.rstrip()
query = createquery(
'SELECT ?subject WHERE { ?subject <http://sybig.de/tfclass#name> "'
+ protein.strip() + '"}')
query_out = rq.get(FUSEKI_URL,
params={
'format': 'json',
'query': query
})
query_out_json = query_out.json()
for element in query_out_json['results']['bindings']:
protein_uri = element['subject']['value']
# protein_uri = protein_uri.replace("localhost", "coyote")
turtlefile = rq.get(protein_uri).text
print(protein_uri + " ----- " + dbd)
with open("temp_turtle", "w") as update:
update.write(turtlefile)
update.write('\n<' + protein_uri + '> sybig:dbd "' + dbd +
'" .')
os.system(
'curl -X PUT -H "Content-type: text/turtle" --data-binary "@temp_turtle" "'
+ protein_uri + '"')
import requests as rq
from queryCreator import createquery
from database import FUSEKI_URL
with open('TF_ids.tsv', "w") as tsvfile:
tf_list = []
query = createquery('SELECT ?subject WHERE {?subject sybig:tfclass_id ?o}')
tf_list_unparsed = rq.get(FUSEKI_URL,
params={
'format': 'json',
'query': query
})
tf_list_json = tf_list_unparsed.json()
# print(tf_list_json)
for x in tf_list_json['results']['bindings']:
tf_list.append(x['subject']['value'])
tf_list.sort()
tsvfile.write("TFClass_ID\tTF_Label\tConsensus Sequence\n")
res_list = []
last_triple = []
for tfc in tf_list:
# print("Found " + tfc)
query = createquery('SELECT ?n ?o ?i WHERE\n {<' + tfc +
'> sybig:consensus_sequence ?i . \n' + '<' + tfc +
'> rdfs:label ?o . \n' + '<' + tfc +
'> sybig:tfclass_id ?n}')
# print("Created query: " + query)
res = rq.get(FUSEKI_URL, params={'format': 'json', 'query': query})
data = res.json()
if data['results']['bindings']: # Non-empty result