Strategic Research

Computational Genomics

The goal of the Computational Genomics group is to take advantage of computing resources to contribute to the general understanding of the biology of genomes in the context of human disease. We are focused in the design, development, and use of bioinformatic protocols and tools to understand the relationship between genome variation and development of disease, mostly cancer. These approaches are also designed to provide work flows and approaches with clinical application in the context of Precision Medicine.

Main projects

  • 1.

    Cancer Genomics

    In the context of different international consortia we are developing and applying analysis tools and approaches to seed light on the underlying genomic and functional basis of several types of tumors. While understanding the biology of tumors and to find particular and personalized therapies, our contribution to the field is centered in the computational analysis of variation at different levels. We have recently developed SMuFin (for Somatic MUtation FINder), a reference-free method for the identification of genomic mutations that are responsible for the development and progression of tumors.

  • 2.

    Human Genetic Variability and complex diseases

    We are also developing and applying computational tools to answer biomedical questions to better understand complex diseases by using all types of genetic and genomic data. Particularly, we have been working on generating efficient and accurate computational strategies to better understand the association between human genetic variability and complex diseases. For example we have developed and applied several strategies and computational methods to enhance the analysis of genomic information for genome-wide association studies (GWAS).



Bioinformatics expertise:

Group Leader:

David Torrents