Biography

I am a postdoctoral researcher at the High-Dimensional Statistical Modeling Team, led by Makoto Yamada.

My goal is to find genetic predictors of disease that are useful for diagnosis, treatment, and understanding the disease’s biology. Traditionally, complex diseases like Alzheimer’s disease are studied through genome-wide association studies ( GWAS). However, conventional GWAS have failed to find a significant share of those genetic causes. I am interested in closing this gap by researching machine learning methods that extract more information from GWAS. Specifically, I superimpose GWAS information onto biological networks. Then, I explore such networks considering both the statistical association of each genetic factor - obtained from GWAS - and the biological context - obtained from the network. However, there are many open questions about how to do this, for instance:

• How to exactly integrate GWAS information with networks?
• What is the right strategy to find truly associated genetic factors? Which underlying assumptions are warranted?
• What sources of information should we consider when building those networks?
• What is the suitable unit of analysis? The SNP? The gene? The pathway?

With my multidisciplinary background in machine learning, statistical genetics, and biotechnology, I believe I am in a privileged position to tackle such questions