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We are interested in developing new approaches for integrating of omics data with applications for biomarker discovery, patient stratification and classification, among others. Some of these methods are available as public bioinformatics tools that can be used by researchers to study and interpret their data.

Statistical & ML methods for Multi-Omics Data Integration

One of our aims is to develop new statistical, computational and machine learning methods for the integration and analysis of heterogeneous omics data in a broad range of contexts:

  • Integrating multi-omics data from different sources.
  • Statistical Methods and computational tools for meta-analysis studies.
  • Tools and methods for Drug Repurposing from Gene Expression Signatures.
  • Pathway analysis and Network analysis

Dissecting the Molecular Basis of Complex Diseases

We closely collaborate with experimental groups to analyze and integrate large-scale biological datasets in order to get a better understanding of the molecular mechanisms of complex diseases.

  • Biomarker Discovery 
  • Patient stratification and disease classification
  • Drug discovery and Pharmacogenomics

Projects and Networks

We are part of different international projects and networks including:

TransBioNet, the Translational Bioinformatics Network coordinated by the Spanish National Bioinformatics Institute (INB) has been created as the reference network for Translational Bioinformatics that brings together most of the bioinformatics units and groups working at health care settings.

 – 3TR. Largest-ever Innovative Medicine Initiative 2 (IMI2) immunology project coordinated by Dr. Alarcón-Riquelme that aims to improve disease management of non-responders to therapy across seven immune-mediated diseases. 3TR will have access to an unprecedented quantity of clinical data and samples of more than 50,000 patients across 50 clinical trials, ultimately aiming to discover and verify stratification biomarkers to improve patient management.