add intepretation tool

-adj_matrix.csv
-first_matrix_connection_GO.csv
-go_level.csv
 X_test.npz
 X_train.npz
+filesforNNarch.zip
 __pycache__/

@@ -20,6 +20,8 @@ The full dataset can be downloaded on ArrayExpress database under the id [E-MTAB
 
 [test set](https://entrepot.ibisc.univ-evry.fr/f/057f1ffa0e6c4aab9bee/?dl=1) 
 
+Additional files for NN architecture: [filesforNNarch](https://entrepot.ibisc.univ-evry.fr/f/6f1c513798df41999b5d/?dl=1) 
+
 ### Usage
 
 Deep GONet was achieved with the $L_{GO}$ regularization and the hyperparameter $\alpha=1e^{-2}$.  
@@ -81,3 +83,7 @@ Without regularization:
 ```bash
 python DeepGONet.py --alpha=0 --EPOCHS=100 --is_training=True --display_step=5 --save=True --processing="train"
 ```
+
+###  Interpretation tool
+
+Please see the notebook entitled *Interpretation_tool.ipynb* to perform the biological interpretation of the results.
\ No newline at end of file

@@ -12,4 +12,5 @@ scipy==1.2.0
 seaborn==0.9.0
 tensorflow==1.12.0
 tensorflow-gpu==1.12.0
-tqdm==4.36.1
\ No newline at end of file
+tqdm==4.36.1
+innvestigate==1.0.8