Research Keywords

Antimicrobial/antifungal resistance, biophysics, Candida/pathogenic yeast, machine learning, magnetobiology, mathematical/quantitative/computational/systems/synthetic biology, microbial evolution experiments, nongenetic variability, stochastic simulations, synthetic gene networks.

Antimicrobial Resistance

Utilizing biophysical modeling, genetically engineered budding yeast (Saccharomyces cerevisiae) habouring synthetic gene networks, and pathogenic fungi (Candida species) to investigate nongenetic drug resistance and the evolution of antimicrobial tolerance/resistance.

Selected Publications:

Identification and elimination of antifungal tolerance in Candida auris.

S. Rasouli Koohi, S.A. Shankarnarayan, C. M. Galon, and D.A. Charlebois. Biomedicines, 11: 898 (2023).

Non-genetic resistance facilitates survival while hindering the evolution of drug resistance due to intraspecific competition.

J. Guthrie and D.A. Charlebois. Physical Biology, 19: 066002 (2022).

Does transcriptional heterogeneity facilitate the development of genetic drug resistance?

K.S. Farquhar, S. Rasouli Koohi, and D.A. Charlebois. Bioessays, 43: 2100043 (2021).

Machine Learning

Training machine learning models to quickly and accurately identify human fungal pathogens and to detect drug resistance.


Machine learning to identify clinically relevant Candida yeast species.

S.A. Shankarnarayan and D.A. Charlebois. Medical Mycology, 62: myad134 (2024).

Machine learning for antimicrobial resistance research and drug development.

S.A. Shankarnarayan, J. Guthrie, and D.A. Charlebois. The Global Antimicrobial Resistance Epidemic – Innovative Approaches and Cutting-Edge Solutions, Guillermo Téllez (Ed.), ISBN: 978-1-80356-042-7 (2022).


Developing spatiotemporal algorithms, building bioelectromagnetic devices, and performing experiments on yeast to study the effects of electromagnetic fields on cellular growth, division, and gene expression, as well as fungal mat formation.


Lattice-based Monte Carlo simulation of the effects of nutrient concentration and magnetic field exposure on yeast colony growth and morphology.

R. Hall and D.A. Charlebois. In Silico Biol., 14: 53-69 (2021).