A genome-scale metabolic network of Saccharomyces cerevisiae was reconstructed using genomic, biochemical, and physiological data. The network includes 708 ORFs, 1035 metabolic reactions, and 584 metabolites, representing approximately 16% of all characterized ORFs in S. cerevisiae. The network was compartmentalized into cytosol and mitochondria, with transport steps between compartments and the environment included. The reconstructed network was compared with Escherichia coli's genome-scale model, showing differences in metabolic capabilities. The network was validated against experimental data from chemostat cultures, demonstrating its accuracy. The model allows for the simulation of cellular behavior under various genetic and physiological conditions, aiding in metabolic engineering strategies. The network includes 1175 reactions and 584 metabolites, with 595 ORFs having enzyme commission (EC) numbers. The model also includes 140 reactions based on biochemical evidence, with a focus on transport reactions and amino acid, nucleotide, and vitamin metabolism. The network was used to evaluate the metabolic capabilities of S. cerevisiae in producing precursor metabolites and amino acids, showing that it is more efficient than E. coli in these processes. The model provides a foundation for further research into eukaryotic metabolic networks and has potential applications in systems biology, drug target identification, and microbial strain design. The reconstruction process involved extensive literature review, database consultation, and biochemical pathway analysis. The model was validated using linear programming and shadow price analysis, ensuring its accuracy and reliability. The study highlights the importance of integrating multi-level biological data to understand cellular functions and improve metabolic engineering strategies. The reconstructed network represents a significant step toward characterizing the entire metabolic portfolio of eukaryotic organisms.A genome-scale metabolic network of Saccharomyces cerevisiae was reconstructed using genomic, biochemical, and physiological data. The network includes 708 ORFs, 1035 metabolic reactions, and 584 metabolites, representing approximately 16% of all characterized ORFs in S. cerevisiae. The network was compartmentalized into cytosol and mitochondria, with transport steps between compartments and the environment included. The reconstructed network was compared with Escherichia coli's genome-scale model, showing differences in metabolic capabilities. The network was validated against experimental data from chemostat cultures, demonstrating its accuracy. The model allows for the simulation of cellular behavior under various genetic and physiological conditions, aiding in metabolic engineering strategies. The network includes 1175 reactions and 584 metabolites, with 595 ORFs having enzyme commission (EC) numbers. The model also includes 140 reactions based on biochemical evidence, with a focus on transport reactions and amino acid, nucleotide, and vitamin metabolism. The network was used to evaluate the metabolic capabilities of S. cerevisiae in producing precursor metabolites and amino acids, showing that it is more efficient than E. coli in these processes. The model provides a foundation for further research into eukaryotic metabolic networks and has potential applications in systems biology, drug target identification, and microbial strain design. The reconstruction process involved extensive literature review, database consultation, and biochemical pathway analysis. The model was validated using linear programming and shadow price analysis, ensuring its accuracy and reliability. The study highlights the importance of integrating multi-level biological data to understand cellular functions and improve metabolic engineering strategies. The reconstructed network represents a significant step toward characterizing the entire metabolic portfolio of eukaryotic organisms.