Mathematical Oncology: Models, analysis and simulations
We intend to address a number of problems of relevance in Oncology from the point of view of mathematical modelling. We will build mathematical models incorporating the essential biological features of the problems under study, which include tumor heterogeneity, gliomas and medical imaging and spatiotemporal models in different types of cancers. We intend to provide both relevant methodological contributions and results of interest for the applications.
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 intend to address different problems in the broad field of
mathematical oncology, which aim to lay the groundwork for further application studies.
The researchers working on this project are MOLAB members Alicia Martínez-González, Gabriel F. Calvo, Juan Belmonte-Beitia, Ignacio Ramís, Julián Pérez-Beteta, David Molina, Araceli Henares, Arturo Álvarez-Arenas, Víctor M. Pérez-García (PI) and some external coworkers including Alfonso Caiazzo (Weirstrasss Institute, Berlin), Milica Pesic (Institute for Biological Problems), Philippe Schucht (Bern University Hospital), Philip Maini (University of Oxford) and Luis Pérez-Romasanta (Hospital de Salamanca)
Beyond this project
The methodological advances provided by this project will be used on the different application fields of interest of the MOLAB group. Hopefully, they will lead to proposals to be validated and tested in clinical studies.