I received my Ph.D. degree from TECNUN, the Engineering School of the University of Navarra, in 2015. My research was focused on the study of metabolic networks with different mathematical tools, especially linear programming techniques, and its application on drug target discovery.
In 2016, I joined Saez-Rodriguez group at the JRC COMBINE lab as a Post-Doc to work on the PrECISE EU project. This project aims to improve patient risk-stratification and treatment in prostate cancer by developing new computational approaches to exploit next generation molecular data.
My research interests involve the application of mathematical and modeling techniques to cancer research. Machine learning techniques applied to biomedical research hold great promise, but also face great challenges because of the low number of samples and the high dimensionality of the experimental data. On top of that, in order to design efficient intervention strategies, not only a predictive model is required, but also a mechanistic understanding of the biological events observed. An appropriate incorporation of prior biological knowledge into different analysis pipelines can help in this regard. Ultimately, the challenge is to efficiently leverage techniques and knowledge gained during many years of biomedical research into results that make an impact in the clinical setting.
|2016-present||PostDoc researcher, JRC-COMBINE, Saez-Rodriguez Group. (PrECISE EU Project)|
|2012-2015||Ph.D. in Bioinformatics. TECNUN – University of Navarra, San Sebastian, Spain (Advisor: F.J. Planes)|
|2011-2012||Master’s degree in Research in Applied Engineering. TECNUN – University of Navarra, San Sebastian, Spain|
|2006-2011||‘Licenciatura’ (MS) in Mechanical Engineering. TECNUN – University of Navarra, San Sebastian, Spain.|