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-rwxr-xr-xserver.py37
1 files changed, 33 insertions, 4 deletions
diff --git a/server.py b/server.py
index 9f68e22..f16d930 100755
--- a/server.py
+++ b/server.py
@@ -10,6 +10,7 @@ import tempfile
import random
import string
from ratspub import *
+from nlp import *
import time
import os
import re
@@ -540,6 +541,10 @@ def sentences():
edge=request.args.get('edgeID')
(tf_name, gene0, cat0)=edge.split("|")
out3=""
+ out5_pl=""
+ out5_sn=""
+ out_pos = ""
+ out_neg = ""
num_abstract = 0
with open(tf_name, "r") as df:
all_sents=df.read()
@@ -550,13 +555,37 @@ def sentences():
out3+= "<li> "+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
num_abstract += 1
if(pmid+cat0 not in pmid_list):
- pmid_list.append(pmid+cat0)
+ pmid_list.append(pmid+cat0)
+ if(cat0=='stress'):
+ out5_pl = 'These are analyzed by deep learning to seperate the relevant sentences.'
+ out5_sn = 'This is analyzed by deep learning to see whether it is relevant or not.'
+ out_pred = "<li> "+ text + " <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/?term=" + pmid +"\" target=_new>PMID:"+pmid+"<br></a>"
+ out4 = predict_sent(out_pred)
+ if(out4 == 'pos'):
+ out_rel = "<b>Relevant sentences:</b>"
+ out_pos += out_pred
+ else:
+ out_irrel = "<br><br><br><hr>"+"<b>Irrelevant sentences:</b>"
+ out_neg += out_pred
out1="<h3>"+gene0 + " and " + cat0 + "</h3>\n"
if len(pmid_list)>1:
- out2 = str(num_abstract) + ' sentences in ' + str(len(pmid_list)) + ' studies' "<hr>\n"
+ out2 = str(num_abstract) + ' sentences in ' + str(len(pmid_list)) + ' studies' + "<br>"
+ if(out5_pl!=""):
+ out2 += out5_pl
+ out2 += "<hr>\n"
else:
- out2 = str(num_abstract) + ' sentence in ' + str(len(pmid_list)) + ' study' "<hr>\n"
- out= out1+ out2 +out3
+ out2 = str(num_abstract) + ' sentence in ' + str(len(pmid_list)) + ' study' "<br>"
+ if(out5_sn!=""):
+ out2 += out5_sn
+ out2 += "<hr>\n"
+ if(out_neg == "" and out_pos == ""):
+ out= out1+ out2 +out3
+ elif(out_pos != "" and out_neg!=""):
+ out = out1 + out2 + out_rel+out_pos + out_irrel + out_neg
+ elif(out_pos != "" and out_neg ==""):
+ out= out1+ out2 + out_rel + out_pos
+ elif(out_neg != "" and out_pos == ""):
+ out = out1 +out2+out_irrel+out_neg
return render_template('sentences.html', sentences="<ol>"+out+"</ol><p>")
## show the cytoscape graph for one gene from the top gene list