Multi-level dynamical modelling of epithelia homeostasis

We construct and analyse mathematical models to understand the mechanisms and design and optimize treatment strategies for maintaining and recovering epithelial homeostasis. We integrate clinical and experimental data into bottom-up, mechanistic, and quantitative models encoded as coupled non-linear dynamical systems. Our mathematical models encompass different timescales simultaneously, allowing us to reproduce gradual pathogenic transitions as emerging properties of the dynamical coupling between biochemical-level regulatory networks and micro-environmental changes.

Research Outline

WPI project plan

Develop and analyse

multi-scale mechanistic  mathematical models of epithelial tissues such as the glandular epithelia of liver and pancreas, the pigmented epithelium of the retina, and the germinal epithelium of the ovary, using clinical and omics data derived from patients and organoids, to contribute to the understanding, prevention and treatment of multifactorial diseases.

Achievement: I have successfully applied my integrative systems biology approach to uncover pathological mechanisms and to design optimal treatment strategies of several epithelial tissue diseases  including Atopic dermatitis ^2,5, tuberculosis ¹, upper airway infection by Streptococcus pneumoniae ³, and carcinomas ⁴.

References

1. Eliezer Flores-Garza et al, 2022. Frontiers in Systems Biology 2:912974.
2. G. Tanaka et al, 2018, Journal of Theoretical Biology 448: 66-79.
3. E. Domínguez-Hüttinger et al, 2017.  Front. Physiol. 8: 115, pp.1–14.
4. L. F. Méndez-López et al, 2017. BMC Syst. Biol., 11(24), p. p.1–15.
5. E. Domínguez-Hüttinger et al, 2017. J. Allergy Clin. Immunol 139:1861-72