Sara Benito-Vaquerizo

GEMsembler combines multiple metabolic models to improve predictions of gene essentiality and auxotrophy by analyzing and integrating features from different reconstruction tools.

This study investigates why engineered E. coli strains for formate utilization do not reach theoretical biomass yields and identifies metabolic bottlenecks and evolutionary changes to improve them.

The paper introduces FROG analysis to standardize reproducibility assessments of genome-scale metabolic models, resulting in full reproducibility of all tested models.

This study evaluates COBRA-based tools for microbial consortia modeling using FAIR criteria and experimental data, finding that newer, better-documented tools generally outperform older ones in quality and performance.

Standard-GEM provides a template for reproducible genome-scale metabolic model development following FAIR principles and software best practices.

The paper engineers a synthetic one-carbon fixation pathway in Cupriavidus necator that achieves higher biomass yield than the native Calvin Cycle.

This study develops a genome-scale metabolic model for Anaerotignum neopropionicum to understand ethanol metabolism via the acrylate pathway and validate it with experimental data.

The paper develops a genome-scale metabolic model of a co-culture of Clostridium autoethanogenum and Clostridium kluyveri to optimize syngas conversion to medium-chain fatty acids.