Ioannis G. Kevrekidis

This study compares kinetic and stoichiometric models of CHO metabolism, finding that kinetic models better predict bioprocess outcomes like cell density and metabolite levels.

This study analyzes noise in biomolecular topologies that implement derivative-action signal differentiation, showing that noise amplification can be avoided.

This paper develops a digital twin model to optimize targeted alpha-particle therapies using antibody-radioconjugate cocktails, showing improved tumor spheroid growth inhibition with mixed affinity conjugates.

This paper designs a PIDA control scheme as a chemical reaction network to improve dynamic performance and steady-state tracking in biochemical systems.

The paper addresses delivery heterogeneity in tumors by developing carrier cocktails that achieve spatial delivery uniformity through complementary delivery properties.

The paper introduces a periodicity scoring algorithm for p53 time series and shows its correlation with cell division events.

The paper develops a semi-supervised learning framework to integrate heterogeneous biological data and demonstrates its application in analyzing Drosophila pattern formation.