Saratram Gopalakrishnan

The paper develops human ME-Models that integrate gene expression and metabolism, showing improved growth-rate predictions and biological plausibility in cancer cell lines.

The paper presents iCHO3K, a comprehensive metabolic model of Chinese Hamster cells, and uses it to analyze metabolic changes in lactate-free cells, identifying structural insights into metabolic rewiring.

COSMIC-dFBA predicts cell density, antibody titer, and metabolite concentrations in bioreactors by integrating machine learning with genome-scale metabolic models.

The paper evaluates algorithms for generating context-specific metabolic models using gene expression data and identifies guidelines for selecting the best models.

K-FIT accelerates kinetic parameterization using steady-state fluxomic data, achieving a thousand-fold speed-up over meta-heuristic methods for E. coli metabolic models.