Maria Suarez Diez

The paper introduces a simplified cFBA method to predict microbial community composition, growth rates, and metabolic interactions by reducing species metabolism to macrochemical equations.

The paper develops a pyruvate biosensor in E. coli using Design-Build-Test-Learn cycles, achieving improved dynamic range and reduced leaky expression.

This paper develops a genome-scale metabolic model for Nannochloropsis oceanica to study lipid production under light acclimation conditions.

This study improves microbial oil fatty acid composition in yeast through genetic modification and cultivation parameter optimization.

MiGenPro trains machine learning models to predict microbial traits from annotated genomes using linked data and semantic frameworks.

This study examines the time-dependent gene expression changes in earthworms exposed to ZnO and ZnO:Mn nanomaterials, revealing transient effects on muscle biology and energy metabolism.

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.

This study improves lipid production in Yarrowia lipolytica using a DBTL approach by combining metabolic model predictions with genetic and medium modifications.

The paper evaluates residual variance structures in toxicokinetic models for predicting chemical uptake and elimination in invertebrates, showing that choosing appropriate variance functions improves model accuracy.

This study enhances malonyl-CoA availability in Pseudomonas putida through multi-level optimization, achieving a 5.8-fold increase in phloroglucinol production.

This study improves lipid production in Cutaneotrichosporon oleaginosus through genetic modifications and fermentation optimization, achieving high lipid content and productivity.

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

The paper identifies aroB as a bottleneck in pABA production in Pseudomonas putida by using combinatorial engineering and statistical modeling to optimize the shikimate pathway.

The paper reports an improved genome sequence and annotation of Cutaneotrichosporon oleaginosus ATCC 20509 to support its use as a biotechnological platform for microbial oil production.

This paper improves microbial oil production in C. oleaginosus by identifying genetic targets and medium supplements through a DBTL approach, achieving up to 56% lipid content.

This paper optimizes curcuminoid production in Pseudomonas putida using dynamic modeling and gene expression tuning, achieving a 4.1-fold increase in efficiency.

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.

This study optimizes fatty acid production in oleaginous yeasts by identifying optimal C/N ratios and temperatures using RSM and analyzing fatty acid composition changes.

The paper predicts Mycoplasma tissue and host specificity using genome sequences by identifying key proteins and functional groups associated with specific infections.

This study analyzes the adaptability and robustness of Mycoplasma pneumoniae's central carbon metabolism using metabolomics data and a dynamic model, identifying key control hubs.

The paper uses metabolic modeling to compare plant-associated Pseudomonas strains and identifies metabolic differences between beneficial and pathogenic species.

The paper uses genome properties and machine learning to classify Pseudomonas strains as plant-beneficial or pathogenic, identifying 28 key features that distinguish these phenotypes.

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.

SALARECON links the Atlantic salmon genome to metabolic fluxes and growth, showing that marine feed efficiency can be achieved by supplementing plant- and insect-based feeds with specific amino acids.

This study uses a genome-scale metabolic model to design serum-free media for Mycoplasma pneumoniae, enabling growth and supporting vaccine production.

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.

The paper identifies a fungal citrate exporter in Aspergillus niger by comparing gene expression under different citrate-producing conditions and validating its function in yeast and the fungus itself.

This study examines name inconsistencies and ambiguities in biochemical databases used for genome-scale metabolic modeling, finding up to 83.1% inconsistency and proposing solutions for better mapping.

The paper evaluates network inference algorithms on metabolite-metabolite association networks using simulated data from a dynamic metabolic model of arachidonic acid.