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SUPREME COURT OF CANADA

def generate_features(kg5_file_path): # Load the KG5 file kg5_data = pd.read_csv(kg5_file_path, sep='\t')

# Assume the columns are gene_product_id, go_term_id, and evidence_code gene_product_features = {}

if gene_product_id not in gene_product_features: gene_product_features[gene_product_id] = []

return feature_df

# Further processing to create binary or count features # ...

Kg5 Da File ✪ <FRESH>

def generate_features(kg5_file_path): # Load the KG5 file kg5_data = pd.read_csv(kg5_file_path, sep='\t')

# Assume the columns are gene_product_id, go_term_id, and evidence_code gene_product_features = {} kg5 da file

if gene_product_id not in gene_product_features: gene_product_features[gene_product_id] = [] kg5 da file

return feature_df

# Further processing to create binary or count features # ... kg5 da file