Arvind Murugan

This paper introduces HiDenSeq, a DNA-barcoded Luria-Delbrück assay that uses deep sequencing to analyze adaptation mechanisms by resolving the Luria-Delbrück distribution over four orders of magnitude.

The paper identifies a molecular mechanism for non-genetic learning in single cells using reversible interaction networks and autoregulatory training rules.

The paper shows that minimizing co-growth between species predicts community robustness across different ecological models.

This paper develops a framework of living circuits using ecosystems as a model, showing that adaptive rules enable phase transitions and near-maximal dissipation in nonequilibrium systems.

This paper introduces a model to study microbial community dynamics by focusing on physiological state transitions rather than fixed interactions, identifying key features of dynamic coexistence.

The paper shows microbial functional guilds respond cohesively to rapid environmental fluctuations and competitively to slower ones, offering a framework for discovering guilds through nutrient perturbations.

This study examines the evolution of mutation rates in proofreading polymerases by controlling direct and indirect selection, revealing dynamic evolutionary features and trade-offs between mutation rates and short-term fitness.

The paper develops a mathematical model to show how promiscuous ligand-receptor interactions enable efficient cellular addressing through combinatorial signaling.

The paper shows NF-κB differentiates cytokine input doses by using negative feedback loops to track changes in concentration rather than absolute levels.