Cleo Kontoravdi

This paper uses Ensemble Kalman Filters to estimate intracellular nucleotide sugar donors in CHO cell cultures from extracellular measurements, improving metabolic state inference.

This paper develops a metabolism-informed bioreactor model to transfer knowledge from fed-batch to continuous biomanufacturing by predicting intracellular fluxes and extracellular concentrations.

The paper applies the Ensemble Kalman Filter to bioprocessing, enabling mechanistic model adaptation across different CHO cell culture systems using a single dataset.

STAMPS designs novel mammalian signal peptides to enhance protein secretion, outperforming existing benchmarks in multiple cell lines.

This paper introduces ObjFind-M, an inverse optimization framework that infers reaction-level metabolic objectives from fluxomic and metabolomic data in mammalian cells, finding mitochondrial ATP synthase as a central driver.

This study shows that nicotinamide reduces lactate accumulation and improves metabolic efficiency in Chinese hamster ovary cell cultures by reversing the Warburg effect.

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.

This study investigates degradation bottlenecks and resource competition in mammalian cells using degron tags, showing that degradation rates of proteins are coupled due to competition for cellular resources.

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

The paper introduces CHOmpact, a reduced metabolic model of CHO cells that improves interpretability and physiological consistency compared to large-scale models.

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