Óscar Dias

The paper presents the first curated genome-scale metabolic model for L. rhamnosus GG, validated using multiple approaches and provides insights into its nutrient requirements and secretions.

This paper reconstructs and validates a genome-scale metabolic model for C. neoformans, identifying potential drug targets based on its unique metabolic features.

PhageDPO is a machine learning tool that predicts depolymerases in bacteriophage genomes to aid in discovering novel antibacterial agents.

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

The paper reconstructs and validates the first genome-scale metabolic model for Vitis vinifera, integrating RNA-Seq data to create tissue-specific models and explore ML-driven fluxomics analysis.

BioISO is a tool that aids in the manual curation of genome-scale metabolic models by reducing search spaces and improving debugging through recursive algorithms and flux balance analysis.

This study uses genome-scale models to optimize chondroitin production in E. coli, achieving up to 535 mg/L in fed-batch fermentation.

The paper updates a genome-scale metabolic model for Xylella fastidiosa subsp. pauca, validating it against experimental data for aerobic metabolism and gum production.

merlin v4.0 improves genome-scale metabolic model reconstruction with new algorithms and tools, supporting multiple organisms and offering competitive performance.

OrtSuite predicts microbial interactions based on genomic content for specific ecosystem processes using ortholog clustering and user-defined functions.

TranSyT automates the integration of transport reactions into genome-scale metabolic models by compiling curated transporter data and providing rapid genome annotation.

This paper develops the first multi-tissue diel genome-scale metabolic model for Quercus suber, highlighting suberin biosynthesis pathways and enabling analysis of tissue interactions.