added columns

model/framework/code/main.py

@@ -41,6 +41,6 @@ def my_model(smiles_list):
 # write output in a .csv file
 with open(output_file, "w") as f:
     writer = csv.writer(f)
-    writer.writerow(["MIC50_10uM", "MIC50_20uM", "MIC90_10uM", "MIC90_20uM", "WCS_50%"])  # header with column names
+    writer.writerow(["mic50_10um", "mic50_20um", "mic90_10um", "mic90_20um", "wcs_50_percent"])
     for o1, o2, o3,o4,o5 in zip(output1, output2, output3, output4, output5):
         writer.writerow([o1, o2, o3, o4, o5])

model/framework/columns/run_columns.csv

@@ -0,0 +1,6 @@
+name,type,direction,description
+mic50_10um,float,high,Classification score for the minimum inhibitory concentration (MIC) of the compound that inhibits 50% of the Mtb population at 10um
+mic50_20um,float,high,Classification score for the minimum inhibitory concentration (MIC) of the compount that inhibits 50% of the Mtb population at 20um
+mic90_10um,float,high,Classification score for the minimum inhibitory concentration (MIC) of the compound that inhibits 90% of the Mtb population at 10um
+mic90_20um,float,high,Classification score for the minimum inhibitory concentration (MIC) of the compound that inhibits 90% of the Mtb population at 20um
+wcs_50_percent,float,high,Classification score for the whole cell screen (WCS) 50% inhibition concentration

input.csv → model/framework/examples/input.csv

@@ -1 +1,2 @@
-C[C@@H]1CN(CC(=O)N2CC(C)(C)c3nc(CO)c(Cc4ccc(F)cc4)cc23)[C@@H](CN2CCOC[C@H]2C)CN1
+smiles
+C[C@@H]1CN(CC(=O)N2CC(C)(C)c3nc(CO)c(Cc4ccc(F)cc4)cc23)[C@@H](CN2CCOC[C@H]2C)CN1