# Further processing to create binary or count features # ...
return feature_df
for index, row in kg5_data.iterrows(): gene_product_id = row['gene_product_id'] go_term_id = row['go_term_id'] kg5 da file
# Usage features = generate_features('path/to/kg5_file.kg5') features.to_csv('generated_features.csv', index=False) # Further processing to create binary or count features #
if gene_product_id not in gene_product_features: gene_product_features[gene_product_id] = [] kg5 da file