Hoang V. Dinh

The paper introduces a new genome-scale metabolic model, iHME, which improves prediction of metabolic dependencies in cancer cells with higher accuracy and lower computational cost.

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

This study uses resource balance analysis to evaluate proteome allocation and metabolic fluxes in yeast under different environmental conditions, identifying key limitations in biosynthetic pathways.

The paper shows mitochondrial respiration is more proteome-efficient than aerobic glycolysis in yeast and mammals, with flexibility arising from maintaining a fermentation-capable proteome.

This paper quantifies how uncertainty in biomass coefficients and non-steady-state conditions affect flux balance analysis results.

The paper constructs a genome-scale metabolic model for Rhodosporidium toruloides IFO0880, integrating functional genomics and phenotypic data to improve predictions of gene essentiality and metabolic capabilities.