Browsing by Author "Saa Higuera, Pedro Andrés E."

Now showing 1 - 9 of 9
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    Build Your Bioprocess on a Solid Strain-beta-Carotene Production in Recombinant Saccharomyces cerevisiae
    (2019) López Salinas, Javiera C.; Cataldo von Bohlen, Vicente Francisco; Peña, Manuel; Saa Higuera, Pedro Andrés E.; Saitua, Francisco; Ibaceta, Maximiliano; Agosin T., Eduardo
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    Effective Dissolved Oxygen Control Strategy for High-Cell-Density Cultures
    (2014) Cárcamo, M.; Saa Higuera, Pedro Andrés E.; Torres, J.; Torres, S.; Mandujano, P.; Pérez C., José Ricardo; Agosin T., Eduardo
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    Engineering saccharomyces cerevisiae for the overproduction of beta-Ionone and Its precursor beta-carotene
    (2020) López, J.; Bustos Lizana, Diego Ignacio; Camilo, C.; Arenas Frigolett, Natalia; Saa Higuera, Pedro Andrés E.; Agosin T., Eduardo
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    Expanding Metabolic Capabilities Using Novel Pathway Designs : Computational Tools and Case Studies
    (2019) Saa Higuera, Pedro Andrés E.; Cortes, M.P.; Lopez, J.; Bustos, D.; Maass, A.; Agosin T., Eduardo
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    From reconstruction to C4 metabolic engineering : a case study for overproduction of polyhydroxybutyrate in bioenergy grasses
    (2018) Gomes de Oliveira Dal’Molin, Cristiana; Quek, Lake-Ee; Saa Higuera, Pedro Andrés E.; Palfreyman, Robin; Nielsen, Lars Keld
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    Genomic integration of unclonable gene expression cassettes in Saccharomyces cerevisiae using rapid cloning-free workflows
    (2020) Cataldo von Bohlen, Vicente Francisco; Salgado, Valeria; Saa Higuera, Pedro Andrés E.; Agosin T., Eduardo
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    LooplessFluxSampler: an efficient toolbox for sampling the loopless flux solution space of metabolic models
    (2024) Saa Higuera, Pedro Andrés E.; Zapararte, Sebastian; Drovandi, Christopher C.; Nielsen, Lars K.
    Uniform random sampling of mass-balanced flux solutions offers an unbiased appraisal of the capabilities of metabolic networks. Unfortunately, it is impossible to avoid thermodynamically infeasible loops in flux samples when using convex samplers on large metabolic models. Current strategies for randomly sampling the non-convex loopless flux space display limited efficiency and lack theoretical guarantees. Results: Here, we present LooplessFluxSampler, an efficient algorithm for exploring the loopless mass-balanced flux solution space of metabolic models, based on an Adaptive Directions Sampling on a Box (ADSB) algorithm. ADSB is rooted in the general Adaptive Direction Sampling (ADS) framework, specifically the Parallel ADS, for which theoretical convergence and irreducibility results are available for sampling from arbitrary distributions. By sampling directions that adapt to the target distribution, ADSB traverses more efficiently the sample space achieving faster mixing than other methods. Importantly, the presented algorithm is guaranteed to target the uniform distribution over convex regions, and it provably converges on the latter distribution over more general (non-convex) regions provided the sample can have full support. Conclusions: LooplessFluxSampler enables scalable statistical inference of the loopless mass-balanced solution space of large metabolic models. Grounded in a theoretically sound framework, this toolbox provides not only efficient but also reliable results for exploring the properties of the almost surely non-convex loopless flux space. Finally, LooplessFluxSampler includes a Markov Chain diagnostics suite for assessing the quality of the final sample and the performance of the algorithm.
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    Modeling oxygen dissolution during pulse oxygen additions under oenological conditions.
    (2012) Saa Higuera, Pedro Andrés E.; Pérez C., José Ricardo; Pontificia Universidad Católica de Chile. Escuela de Ingeniería
    Durante fermentaciones enológicas industriales, adiciones discretas de oxígeno son una práctica común para aumentar la tasa de fermentación. Sin embargo, la dosis de oxígeno y el tiempo de la adición deben ser escogidos cuidadosamente para evitar efectos perjudiciales en la calidad del vino. Hasta ahora, las adiciones se llevan a cabo de manera empírica, ya que aún no se entiende completamente la dinámica de disolución del oxígeno en condiciones enológicas. Por lo tanto, para administrar eficientemente las adiciones de oxígeno, en este trabajo se presentan dos modelos de balance de masa de oxígeno capaces de reproducir la evolución de la disolución durante pulsos de adición en fermentaciones enológicas a escala de laboratorio y en condiciones abióticas emulando fermentaciones en una columna de burbujeo. Calibraciones del modelo a escala de laboratorio indican que la tasa específica de consumo de oxígeno de Saccharomyces cerevisiae depende fuertemente de la fase de crecimiento y que el coeficiente de transferencia de masa es influenciado por el consumo biológico.
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    Oxygen Incorporation and Dissolution During Industrial-Scale Red Wine Fermentations
    (2014) Moenne, M. Isabel; Saa Higuera, Pedro Andrés E.; Laurie, V. Felipe; Pérez C., José Ricardo; Agosin T., Eduardo