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 - **results**: Result files of the RepoDB test and the distribution plots (once these are generated).
 - **testData**: Data to validate model using RepoDB.
 - **Code files:**
-  - autoencoder (drug molecular embedder model) 
-  - dmsr (drug repurposing model)
+  - autoencoder (drug molecular embedder model). 
+  - dmsr (drug repurposing model).
   - drug_embedding_generator (generates drug embeddings using SMILES representation).
-  - heterograph_construction (build graph)
-  - testRepoDB (validate model using RepoDB)
-  - topN (get topN new predictions)
-  - utilities (plotting utilities)
+  - heterograph_construction (build graph).
+  - testRepoDB (validate model using RepoDB).
+  - testRepoDBWeightsAndBiases.py (validate model using RepoDB automatically with Weights&Biases).
+  - topN (get topN new predictions).
+  - utilities (plotting utilities).
 
 ## Summary
 Repository of Adrián Ayuso-Muñoz's master's final project "Graph Deep Learning for Drug Repurposing".
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