Mathematical Modelling of Biological Processes

Erida Gjini

The research group on Mathematical Modelling of Biological Processes is interested in mathematical biology with special focus on infectious disease dynamics and control. Adopting mechanistic approaches, they develop a deeper quantitative understanding of how system behavior emerges from the interaction of its components, and how processes at one biological scale affect patterns observed at another. At the evolution-ecology-epidemiology interface, this research links processes at the individual and the population level. Data-driven mathematical models are applied to a variety of topics, including microbial ecology and competition dynamics, within-host interactions in health and disease, vaccination effects in host-pathogen systems and antibiotic resistance.

They study and quantify the role of host immune defences for controlling bacterial infections and for mitigating the ascent of drug-resistance during treatment.This research combines mathematical analysis with computer simulations, as well as tools from population dynamics, stochastic processes, and parameter inference problems, relevant to different areas of biology. The insights from mathematical models can have practical implications for biomedical settings and public health policy. This group currently collaborates with several teams in Portugal (IMM, U. Lisbon) and abroad, including France (University of Tours) and the USA (University of Tennessee, University of Michigan).

Publications

Gjini E. and Madec S. (2021) The ratio of single to co-colonization is key to complexity in interacting systems with multiple strains. Ecol Evol. 2021; 00:1–19
Martins, A.D. and Gjini E. (2020) Modeling Competitive Mixtures With the Lotka-Volterra Framework for More Complex Fitness Assessment Between Strains. Front. Microbiol. 11: 572487