Hi there!
I am Gonzalo (though most people call me Gon), a computational biologist with research expertise in the analysis of high-throughput biological data and cancer multi-omics. I also enjoy teaching bioinformatics and molecular biology.
I studied a BSc in Molecular Biology and Biochemistry at the Universidad Autónoma de Madrid (UAM). During this time, I received a collaboration grant from the Department of Molecular Biology to investigate the relationship between transcriptional regulation and chromatin structural complexes at the CBM Severo Ochoa. This experience sparked my growing interest in translational research and the molecular basis of complex human diseases.
In 2001, I joined to the Applied Molecular Oncology Lab in the Clinical Oncology Department at Hospital Ramón y Cajal, where I completed my PhD studying the transcriptomics of micro-disseminated and metastatic cells in melanoma and prostate cancer patients. There, I was first exposed to cancer research involving high-throughput technologies and multi-omics approaches—and, of course, to the emerging and exciting field of bioinformatics. That experience ultimately led me to formally train in the field, completing an MSc in Bioinformatics and Computational Biology at the Universidad Complutense de Madrid (UCM).
Since 2008, I have held a staff position at the Bioinformatics Unit (BU) of the CNIO. Over the years, I have collaborated on numerous projects with both experimental and computational groups. Between 2014 and 2021, I also served as an associate professor at UAM.
Currently, I combine my research at the BU with teaching responsibilities as Academic Coordinator of the Master’s program in Bioinformatics Applied to Personalized Medicine and Health, organized by the Instituto de Salud Carlos III (ISCIII).
My main scientific interests include:
- Developing new computational methods to predict effective anti-tumor therapies
- Analyzing and interpreting multi-omics data from cancer patients to identify novel biomarkers and mechanisms of drug response.
- Applying bioinformatics approaches to cancer immunotherapy.
