Abstract
Flux Balance Analysis (FBA) is a technique that allows estimation of metabolic fluxes in established conditions, focusing the flux determination as an optimization problem. For this reason, it is important to use an appropiate objective function in order to adjust estimations of FBA with the real behaviour of the cell. The aim of this work was to examine the effect of a set of input data fluxes (among five diferent sets) on the accuracy of predictions obtained with FBA with application in seven different objective functions. In this study, Saccharomyces cerevisiae was selected as model microorganism, and its metabolism was represented at genomic scale using the model iMM904. Accuracy of obtained predictions was evaluated and compared with eight set of experimental data. Results showed that the objective function representing in a better way the cellular behaviour depends on the set of fluxes used as input data.
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Sánchez, C.E.G., Sáez, R.G.T. (2014). Exploration of the Effect of Input Data on the Modeling of Cellular Objective in Flux Balance Analysis (FBA). In: Castillo, L., Cristancho, M., Isaza, G., Pinzón, A., Rodríguez, J. (eds) Advances in Computational Biology. Advances in Intelligent Systems and Computing, vol 232. Springer, Cham. https://doi.org/10.1007/978-3-319-01568-2_8
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DOI: https://doi.org/10.1007/978-3-319-01568-2_8
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-01567-5
Online ISBN: 978-3-319-01568-2
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