Guim Aguadé‐Gorgorió

This study develops a computational framework to model genomic instability in tumors, showing it can both drive evolution and lead to population collapse, with implications for therapy.

This study investigates the effects of synthetic horizontal gene transfer in ecological consortia models to promote biodiversity and regulate gene propagation.

The paper shows that emergent coexistence in ecological communities arises from dense networks of indirect effects in species-rich models with pairwise interactions, revealing a limit to reductionist explanations.

This study presents an eco-evolutionary model showing how tumor mutational burden influences immunotherapy success and resistance through trade-offs between oncogenic and immunogenic mutations.

The paper develops a mathematical model of glioma growth incorporating tumor-associated macrophages to evaluate myeloid-targeted therapies and their combination with radiation.

The paper clarifies that the sublinear growth model does not resolve the species coexistence paradox because it relies on unrealistic assumptions about growth rates at low abundance.

The paper models tumors as ecological communities using the Generalized Lotka-Volterra model to understand intra-tumor heterogeneity and its implications for cancer progression and treatment resistance.

The paper presents a mathematical model to explore the relationship between tumor genetic instability and immune response, showing that increased mutational load and immune migration can lead to cancer clearance.