Research lines

Our research spans three interconnected areas:

• Multi-omics data integration: We develop statistical frameworks and tools to jointly analyze data from heterogeneous omics sources. Some examples of these tools are:
  • MORE, for the inference of multi-layer regulatory networks and compare them across different phenotypes;
  • MOSim, for simulating multi-omic bulk and single-cell data, which is useful to prepare and test pipelines and tools;
  • Coxmos, for the discovery of molecular signatures associated with survival.

• Single-cell and spatial technologies: We build computational methods tailored to the unique challenges of single-cell RNA-seq, long-read sequencing, and spatial transcriptomics data. We are currently adapting our tools to deal with the specific features of these new technologies.

• Clinical and translational applications: We apply our methods to real biomedical problems, including cancer (ovarian, lung), neurodegenerative diseases (Parkinson’s), metabolic disorders (diabetes, hepatic encephalopathy), etc.