Eva Balsa‐Canto

GeNETop: Context-Specific Genome-Scale Constrained Models Using Network Topology, Flux Variability, and Transcriptomics

GeNETop improves context-specific metabolic models by integrating flux variability, network topology, and transcriptomics to enable dynamic simulations.

Identification of dynamic models of microbial communities

This paper presents a methodology to improve dynamic microbial community models by addressing identifiability, stability, and overfitting issues through a comprehensive workflow.

A continuous dynamic genome-scale model explains batch fermentations led by species of the Saccharomyces genus.

This paper introduces a continuous dynamic genome-scale model to predict intracellular fluxes during batch fermentation, capturing all growth phases and secondary metabolism in Saccharomyces species.

Dynamic genome-scale modeling of Saccharomyces cerevisiae unravels mechanisms for ester formation during alcoholic fermentation

The paper uses dynamic flux balance analysis to identify conserved and strain-specific metabolic mechanisms in Saccharomyces cerevisiae that influence ester formation during alcoholic fermentation.

Monod model is insufficient to explain biomass growth in nitrogen-limited yeast fermentation

Adding carbohydrate accumulation to Monod growth and tying fermentation rate to protein lets a yeast kinetic model capture post-nitrogen-depletion biomass gains that Monod alone misses.

A multi-phase multi-objective dynamic genome-scale model shows different redox balancing among yeast species in fermentation

The paper develops a dynamic genome-scale model to compare redox balancing strategies in yeast species during fermentation, revealing novel metabolic pathways in cryotolerant strains.

A multi-phase multi-objective genome-scale model shows diverse redox balance strategies in yeasts

This paper develops a dynamic genome-scale model to analyze redox balance strategies in yeasts during batch cultures, showing how cryotolerant strains achieve metabolic stability.