This repository contains computational tools and metabolic models developed for the study "GAN-Enhanced Machine Learning and Metabolic Modeling Identify Reprogramming Signatures and Vulnerabilities in Pancreatic Cancer". The framework integrates:

• Genome-scale metabolic models (GSMs) of 144 PDAC and 144 healthy samples
• WGAN-GP synthetic healthy data generation with biological validation
• Random Forest classifier for PDAC metabolic signature identification
• Multi-level analysis of pathway, reaction, and gene alterations