Cancer Modelling Group

To propose new models relevant to experimental biologists and clinicians and develop the analytical and computational tools necessary for their analysis. We pay special attention to problems with clinical relevance, in particular those related to cancer.

Team leaders
Tomas Alarcon Cor
Principal Investigator  -  CRM
Research team
Daria Stepanova
PhD Student  -  CRM
Aurora Hernandez-Machado
CRM
Lourdes Elvira Mendez Mora
CRM
Stefano Pedarra
PhD Student  -  CRM
Computational & Mathematical Biology
External collaborators
Helen Byrne
University of Oxford
Pilar Guerrero Contreras
Universidad Carlos III Madrid
Philip K. Maini
University of Oxford
Karen M Page
University College London
Juan Calvo
Universidad de Granada
General information

Most phenomena studied by the Natural Sciences, from Material Sciences to Astrophysics, are multi-scale processes, i.e. they involve the coupling of multiple different processes characterised by widely-ranging time and length scales, with the macroscopic behaviour emerging from the complex interactions between them. Whilst considerable progress has been done in dealing with such problems in the Physical Sciences, the success achieved so far in the Biological Sciences is rather more limited. This is partly due to the fact that the individual components of biological systems (e.g. cells) are much more complex than their counterparts in physical systems and, therefore, new methods and models are needed to analyse multi-scale processes in Biology. Such is the remit of the Computational & Mathematical Biology group at CRM: To propose new models relevant to experimental biologists and clinicians and develop the analytical and computational tools necessary for their analysis. We pay special attention to problems with clinical relevance, in particular those related to cancer.

The research activity of our group is developed along the following lines:

- Multiscale modelling of tumour growth and tumour-induced angiogenesis

- Evolutionary dynamics of populations with complex structure, in particular cell populations with hierarchical structure and genotype-phenotype map

- Mathematical modelling of the cell-cycle

- Stochastic modelling of receptor tyrosine kinases

- Tumour dormancy