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