Dr Eder Zavala PhD

Eder Zavala

Institute of Metabolism and Systems Research
MRC Skills Development Fellow

Contact details

Centre for Systems Modelling and Quantitative Biomedicine
College of Medical and Dental Sciences
University of Birmingham
B15 2TT

Dr Eder Zavala is an MRC Skills Development Fellow jointly appointed across Mathematics, Computer Science, and the Institute of Metabolism and Systems Research. His work focuses on interdisciplinary research spanning mathematics, physics, computer science, biology, biomedical and clinical sciences. In addition to his fellowship award, Eder has secured an ULTRADIAN EU Horizon 2020 secondment to revolutionise the diagnosis and management of endocrine conditions through the use of quantitative methods to analyse hormone rhythms. He has also established international partnerships between Mexico and the UK supported by the Global Challenges Research Fund, and by being co-awarded with a Royal Society Newton Mobility Grant together with other intra-institutional funding. His collaborations range from biomathematics, to healthcare technologies, to philosophy, and span 4 Russell Group UK universities, the University of California San Diego (UCSD), the National Autonomous University of Mexico (UNAM), and the University of Bergen in Norway. Eder is also passionate about public engagement and science communication, speaking in events such as Pint of Science and organising workshops towards the development of communities where researchers, clinicians and patients work together to address current challenges in neuroendocrinology.

He is part of the Centre for Systems, Modelling and Quantitative Biomedicine

Centre Twitter handle - https://twitter.com/SMQB_UoB


  • PhD in Molecular Biomedicine, 2012, CINVESTAV Mexico
  • MSc in Engineering and Biomedical Physics, 2008, CINVESTAV Mexico
  • BSc (Hons) in Physics, 2006, UANL Mexico


Eder is a physicist with a great passion for mathematical biology and biomedicine. While at graduate school at CINVESTAV, Mexico, his research interests revolved around mathematically modelling signalling pathways and gene regulatory networks, focusing on understanding how the topology of these networks influences their dynamics and robustness against noise. During his MSc in Engineering and Biomedical Physics, Eder developed mathematical models of self-regulated gene circuits, exploring how negative and positive regulatory feedback loops affect bacterial phenotypes. While doing his PhD in Molecular Biomedicine, he developed a mathematical model of a somitogenic regulatory network that considers the interactions between antagonistic gradients and genetic clocks that embryonic cells use as spatiotemporal cues to achieve robust, irreversible commitment to a developmental fate.

Later, while at the Okinawa Institute of Science and Technology (OIST) in Japan, Eder investigated non-classic stochastic effects in gene expression and used advanced computational tools to simulate these processes at the single gene level. He also performed spatial stochastic simulations of asymmetric protein segregation in yeast and developed a Delayed Stochastic Simulation Algorithm with cell division (DSSAcd) to explore cell cycle effects in feedback-regulated gene circuits.

In 2015, Eder switched fields to apply his skills to the field of neuroendocrinology at the University of Exeter, working alongside professors John Terry and Stafford Lightman (FRS). Since then, Eder’s work has focused in developing a mathematical understanding of hormone dynamics in health and disease. This work lead to him securing an MRC Skills Development Fellowship to further his own research plans.


Eder is primarily interested in the mechanisms underpinning neuroendocrine regulation of the Hypothalamic-Pituitary-Adrenal (HPA) axis. His goal is to develop a mathematical understanding of hormone dynamics that includes rhythmic secretion, responses to perturbations, and long-term physio-pathological changes. To do this, he works alongside a range of interdisciplinary collaborators to propose models that offer testable predictions. He has developed mathematical models of the adrenal steroidogenic gene regulatory network that successfully predicts dynamic responses to ACTH perturbations of different magnitude. By including the crosstalk interactions with the immune pathway, his models also explain the sustained glucocorticoid activation observed during the inflammatory stress response.

Currently, Eder is extending this theoretical framework to integrate rhythmicity and stress, while also considering how these processes interact with the metabolic and reproductive endocrine axes. His plan is to continue developing these multiscale mathematical models to understand the dynamic changes elicited by disease, with a focus on understanding the disruption of these mechanisms during stress-related disorders.

Eder is also interested in healthcare technologies for diagnosing and monitoring the progression of illness. To do this, he is developing a quantitative analysis of continuously-sampled 24h ambulatory micro-dialysis hormone profiles to identify novel dynamic biomarkers that signal disease more efficiently than current single time point diagnosis. Eder combines this with the analysis of wearable device data (e.g., physical activity, heart rate, temperature, glucose, and sleep tracking) collected simultaneously with continuous hormone and metabolite microdialysates to characterise the dynamic human chronobiome.

Research Groups and Centres

Centre for Systems Modelling and Quantitative Biomedicine (SMQB)

Other activities

Member of the Mexican National System of Researchers - Level 1 (2016-2018)


Recent publications


Zavala, E, Voliotis, M, Zerenner, T, Tabak, J, Walker, JJ, Feng Li, X, Terry, J, Lightman, SL, O'Byrne, K & Tsaneva-Atanasova, K 2020, 'Dynamic hormone control of stress and fertility', Frontiers in Physiology. https://doi.org/10.1101/2020.08.24.264234

Kim, DW, Zavala, E & Kim, JK 2020, 'Wearable technology and systems modeling for personalized chronotherapy', Current Opinion in Systems Biology, vol. 21, pp. 9-15. https://doi.org/10.1016/j.coisb.2020.07.007

Colombetti, G & Zavala, E 2019, 'Are emotional states based in the brain? A critique of affective brainocentrism from a physiological perspective', Biology and Philosophy, vol. 34, no. 5, 45, pp. 1-20. https://doi.org/10.1007/s10539-019-9699-6

Spiga, F, Zavala, E, Walker, JJ, Zhao, Z, Terry, JR & Lightman, SL 2017, 'Dynamic responses of the adrenal steroidogenic regulatory network', Proceedings of the National Academy of Sciences of the United States of America, vol. 114, no. 31, pp. E6466-E6474. https://doi.org/10.1073/pnas.1703779114

Zavala, E & Marquez-Lago, TT 2014, 'Delays induce novel stochastic effects in negative feedback gene circuits', Biophysical Journal, vol. 106, no. 2, pp. 467-478. https://doi.org/10.1016/j.bpj.2013.12.010

Zavala, E & Marquez-Lago, TT 2014, 'Stochastic Discrete Effects in a Simple Gene Circuit with Delayed Negative Feedback', Biophysical Journal, vol. 106, no. 2, supplement 1, pp. 376a. https://doi.org/10.1016/j.bpj.2013.11.2128

Zavala, E & Marquez-Lago, TT 2014, 'The long and viscous road: uncovering nuclear diffusion barriers in closed mitosis', PLoS Computational Biology, vol. 10, no. 7, e1003725, pp. 1-15. https://doi.org/10.1371/journal.pcbi.1003725

Zavala, E & Santillan, M 2012, 'An Analysis of Overall Network Architecture Reveals an Infinite-period Bifurcation Underlying Oscillation Arrest in the Segmentation Clock', Mathematical Modelling of Natural Phenomena.

Zavala, E & Santillan, M 2011, 'Oscillation arrest in the mouse somitogenesis clock presumably takes place via an infinite period bifurcation', arXiv preprint arXiv:1108.0673.

Other contribution

Zavala, E, Gil-Gómez, CA, Wedgwood, KCA, Burgess, R, Tsaneva-Atanasova, K & Herrera-Valdez, MA 2020, Dynamic modulation of glucose utilisation by glucocorticoid rhythms in health and disease.. https://doi.org/10.1101/2020.02.27.968354

Review article

Zavala, E, Wedgwood, KCA, Voliotis, M, Tabak, J, Spiga, F, Lightman, SL & Tsaneva-Atanasova, K 2019, 'Mathematical modelling of endocrine systems', Trends in Endocrinology and Metabolism, vol. 30, no. 4, pp. 244-257. https://doi.org/10.1016/j.tem.2019.01.008

View all publications in research portal