Predicción a escala genómica de Componentes de Saccharomyces cerevisiae mediante Análisis de Balance de Flujos

several biological models, named reconstructions, are used for the study of the s. cerevisiae microorganism. the reconstructions can be genomic scaled. mathematical models are generated from the reconstructions and they are called stoichiometric models. the flux balance analysis (fba) is one of the tools used for the analysis of these models. the fba attempts to predict the evolution of the microorganism and the consumption and production of components like glucose, ethanol, glycerol, succinate, acetate and pyruvate. a flux variability analysis (fva) is used to determine the uniqueness of the fba predictions. this paper shows the results of applying fba to the imm904 reconstruction of s. cerevisiae and compares them with experimental data from literature. the results in this paper show that it is possible to predict the evolution with errors between 11% and 28% ; the production of co2 with errors between 0.3% and 4.5%; and the production of ethanol with errors between 11% and 13%, using fba for the imm904 model.