###### Decription of the files on GitHub ######

1) RepTB_NBI_algorithm_snippet.ipynb : This python notebook contains only the python code for the NBI algorithm. It takes the Adjacent Matrix (A) created from the file new_dt_from_go_and_db_unique_latest.csv

2) new_dt_from_go_and_db_unique_latest.csv: This file contains the drug-target interactions from drugbank and GO mapping. Create an Adjacent matrix with this file and feed it into NBI.

3) Generating_random_netoworks.m: This is a matlab file that was used to generate random networks with the same number of nodes but varying drug interactions and running through NBI.

4) uniprot_go_annotations_mf_strong_evidence_new.csv: This file contains the mapping of the molecular function GO terms and Uniprot Ids.

5) predicted_targets_for_all_drugs_using_percent_diff_0.20_new.csv: This is our prioritized list of predicted DTIs using NBI.