Biomedicine can only be understood in the context of genomics and with the concourse of bioinformatics. Our department aims to tackle biomedical problems from a system's biology perspective. Following this, the general objective we seek through the main lines of research is to relate mutations to their effect at both cellular and phenotypic level trying to understand the underlying mechanism of action.


Systems Genomics


Genes operate within an intricate network of interactions that we have only recently started to envisage.  Many higher-order levels of interaction are continuously being discovered. In this scenario we are interested in developing methods and tools which can help to understand large-scale experiments from a systems biology perspective.



Genomics of Gene Expression 

Our research focusses on the dynamics and functional aspects of gene expression on the genome scale. We develop statistical approaches for the analysis of multifactorial and time-course gene expression data, focussing on their integration with functional and phenotipic data. Currently, we use Next Generation Sequencing methodologies to analyze the relationship between gene expression and genomics features. We strive to generate user-friendly tools that can routinely be use in experimental labs.


Computational Biology


We are focused on the developement of advance computing solutions to solve issues in genomic data analysis. We are intereseted in developing algorithms, databases and tools for the analysis of genomic data that enable researchers to understand what biological processes or variants are involved in different phenotypes or diseases. Our main lines of reasearch cover among others genomic variant analysis, machine learning, NGS analysis or cloud-based solutions for Big Data.