Kirill S. Korolev

This study uses dynamic flux balance analysis to model cancer cell metabolism, revealing dependencies on growth media and cell-line specificities, and identifying potential therapeutic targets.

This paper develops a dynamical maximum entropy framework to model single-cell metabolic states during E. coli diauxie, revealing co-consumption as a continuous rather than discrete phenomenon.

The paper develops a Bayesian statistical method to infer invasion characteristics of human-dispersed species by integrating life-history dynamics and transportation network data.

The paper models bacterial colony morphology by integrating metabolic reactions and biomass propagation, showing realistic colony shapes and metabolic ring formation.

The paper introduces MIND, a platform for comparing and integrating microbial interaction networks from diverse datasets.