Mathematical Models in Oncology
2020-2023
In this project we addressed several problems of relevance in Oncology from the point of view of mathematical modeling. Mathematical models incorporating the essential biological features of the problems under study were built. Among these problems, we can find tumor heterogeneity, gliomas and medical imaging and spatiotemporal models in different types of cancers. We provided both relevant methodological contributions and results of interest for the applications.
Why Mathematics?
Mathematical models are used in Science and Engineering to create conceptual frameworks in order to understand Nature and provide solutions to real-world problems. Here we addressed different problems in the broad field of mathematical oncology, which laid the groundwork for further application studies.
The Team
The researchers that worked on this project are MOLAB members Alicia Martínez-González, Gabriel F. Calvo, Juan Belmonte-Beitia, Ignacio Ramís Conde, Julián Pérez-Beteta, David Molina, Víctor M. Pérez-García (PI) and María Rosa Durán, together with external collaborators that provided us clinical data and data from experimental models.
Beyond this project
The methodological advances provided by this project are being used on the different application fields of interest of the MOLAB group. They are leading to proposals under testing in clinical studies.
Funded by
