Robert Planqué

This paper develops a mathematical framework to model microbial communities optimizing growth rates through metabolic cooperation and resource allocation.

The paper derives conditions under which microorganisms shift to an inefficient overflow metabolism above a critical growth rate, using a core metabolic model and validating it with yeast data.

The paper investigates whether microbial cells can reduce entropy production rate by shifting to less thermodynamically driven metabolism at faster growth rates, using yeast models and experimental data.

The paper shows that cells can sense their growth rate and optimize it through gene regulatory circuits, supported by analysis of E. coli's use of ppGpp.

This paper introduces ecmtool, a tool that enumerates elementary conversion modes to fully characterize metabolic capabilities from genome-scale networks.

The paper develops a theory to describe all possible molecular states of cellular self-fabrication, identifying Elementary Growth Modes as the fundamental building blocks of cellular phenotype.

The paper shows that overflow metabolism arises from two growth-limiting constraints across different metabolic models.

The paper develops a theory to explain cellular heterogeneity by considering stochastic ancestral events in isogenic cell populations, showing that copy-number noise is unavoidable due to cell division stochasticity.

The paper shows that maximizing microbial growth rate limits the number of active metabolic pathways to the number of enzyme expression constraints, explaining simple metabolic behaviors through evolutionary optimization.

The paper analyzes the stability of a metabolic pathway under qORAC control, showing it achieves a unique and stable steady state with maximal flux.

The paper develops a theoretical framework for optimal metabolic flux maintenance through gene expression control in bacteria, showing that it requires a minimum number of metabolite-regulated transcription factors.

The paper develops new methods for bifurcation analysis of metabolic pathways, applying them to yeast glycolysis to explore steady-state behavior and bistability.