diff --git a/UQ_ML_data.py b/UQ_ML_data.py
index 80c327b..40303f8 100644
--- a/UQ_ML_data.py
+++ b/UQ_ML_data.py
@@ -251,10 +251,10 @@ def setvars(gene,drug):
                , 'ddg_foldx'
                , 'deepddg'
                , 'ddg_dynamut2'
-               , 'mmcsm_lig']
-    
-    foldX_cols = ['contacts'
-    , 'electro_rr', 'electro_mm', 'electro_sm', 'electro_ss'
+               , 'mmcsm_lig'
+               , 'contacts']
+
+    foldX_cols = [ 'electro_rr', 'electro_mm', 'electro_sm', 'electro_ss'
     , 'disulfide_rr', 'disulfide_mm', 'disulfide_sm', 'disulfide_ss'
     , 'hbonds_rr', 'hbonds_mm', 'hbonds_sm', 'hbonds_ss'
     , 'partcov_rr', 'partcov_mm', 'partcov_sm', 'partcov_ss'
diff --git a/pnca_config.py b/pnca_config.py
index 2a75372..db080a4 100755
--- a/pnca_config.py
+++ b/pnca_config.py
@@ -57,3 +57,6 @@ print('Categorical features (n):'
       , categorical_FN
       , '\n================================================================\n')
 print('\n#####################################################################\n')
+
+################################################################################
+
diff --git a/uq_ml_models_FS/scriptfsycm.py b/uq_ml_models_FS/scriptfsycm.py
index 1e2e578..396a4bc 100644
--- a/uq_ml_models_FS/scriptfsycm.py
+++ b/uq_ml_models_FS/scriptfsycm.py
@@ -295,4 +295,65 @@ CVResultsDF_smnc = YC_resD_smnc['CrossValResultsDF']
 CVResultsDF_smnc.sort_values(by=['matthew'], ascending=False, inplace=True)
 BTSResultsDF_smnc = YC_resD_smnc['BlindTestResultsDF']
 BTSResultsDF_smnc.sort_values(by=['matthew'], ascending=False, inplace=True)
+##############################################################################
+yC_gf = run_all_ML(input_pd=X[X_genomicFN], target_label=y, blind_test_input_df=X_bts[X_genomicFN], blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_gfCT_baseline= yC_gf['CrossValResultsDF']
+yc_gfCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_gfBT_baseline = yC_gf['BlindTestResultsDF']
+yc_gfBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
 
+
+# strucF:All
+yC_sfall = run_all_ML(input_pd=X[X_strFN], target_label=y, blind_test_input_df=X_bts[X_strFN], blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_sfallCT_baseline= yC_sfall['CrossValResultsDF']
+yc_sfallCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_sfallBT_baseline = yC_sfall['BlindTestResultsDF']
+yc_sfallBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+
+
+# strucF:Common
+yC_sfco= run_all_ML(input_pd=X[common_cols_stabiltyN], target_label=y
+                   , blind_test_input_df=X_bts[common_cols_stabiltyN]
+                   , blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_sfcoCT_baseline= yC_sfco['CrossValResultsDF']
+yc_sfcoCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_sfcoBT_baseline = yC_sfco['BlindTestResultsDF']
+yc_sfcoBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+
+
+# strucF:common_stability + foldX_cols i.e interaction
+yC_fxss= run_all_ML(input_pd=X[common_cols_stabiltyN+foldX_cols], target_label=y
+                   , blind_test_input_df=X_bts[common_cols_stabiltyN+foldX_cols]
+                   , blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_fxssCT_baseline= yC_fxss['CrossValResultsDF']
+yc_fxssCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_fxssBT_baseline = yC_fxss['BlindTestResultsDF']
+yc_fxssBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+
+
+# strucF:foldX_cols i.e interaction
+yC_fx= run_all_ML(input_pd=X[common_cols_stabiltyN+foldX_cols], target_label=y
+                   , blind_test_input_df=X_bts[common_cols_stabiltyN+foldX_cols]
+                   , blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_fxCT_baseline= yC_fx['CrossValResultsDF']
+yc_fxCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_fxBT_baseline = yC_fx['BlindTestResultsDF']
+yc_fxBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+
+
+# categorical
+yC_cat= run_all_ML(input_pd=X[categorical_FN], target_label=y
+                   , blind_test_input_df=X_bts[categorical_FN]
+                   , blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_catCT_baseline= yC_cat['CrossValResultsDF']
+yc_catCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_catBT_baseline = yC_cat['BlindTestResultsDF']
+yc_catBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+
+
+# Evolutionary
+yC_ev = run_all_ML(input_pd=X[X_evolFN], target_label=y, blind_test_input_df=X_bts[X_evolFN], blind_test_target=y_bts, preprocess = True, var_type = 'mixed')
+yc_evCT_baseline= yC_ev['CrossValResultsDF']
+yc_evCT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)
+yc_evBT_baseline = yC_ev['BlindTestResultsDF']
+yc_evBT_baseline.sort_values(by=['matthew'], ascending=False, inplace=True)