Daniel Machado

This study shows that four bacterial species can coexist across diverse environments through cross-feeding and niche partitioning, challenging the competitive exclusion principle.

This study creates a genome-scale metabolic model atlas for Streptococcus suis, revealing lineage-specific metabolic differences and identifying potential antimicrobial targets.

This paper presents an updated genome-scale metabolic model for Ruminiclostridium cellulolyticum to simulate lignocellulosic biomass fermentation.

This study benchmarks six optimization solvers for genome-scale metabolic modeling, showing open-source solvers can match commercial ones in performance.

Memote, open-source Python software, runs a community-maintained, partly scored test suite (consistency, biomass, annotations, optional experimental data) on SBML-encoded genome-scale metabolic models, once or through continuous integration.

This study benchmarks kinetic models of Escherichia coli metabolism to evaluate their performance in predicting metabolic fluxes under genetic and environmental perturbations.

This study shows how kefir, a natural microbial community, achieves stable coexistence through spatio-temporal niche partitioning and metabolic cooperation during milk fermentation.

CarveMe automates the reconstruction of genome-scale metabolic models for microbial species and communities, achieving performance comparable to manual curation.

The paper identifies phosphorylation sites in metabolic enzymes of FH-deficient cells using proteomics and computational modeling, showing PDHA1 inhibition due to increased phosphorylation.