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 (Carmona-Saez et al., 2017, Toro-Domínguez et al. 2014. Martorell et al., mCSEA. 2019).
- Statistical Methods and computational tools for meta-analysis studies (MetaGENyO and ImaGEO).
- Tools and methods for Drug Repurposing from Gene Expression Signatures (Vazquez et al., 2010, Toro-Domínguez et al., 2017).
- Functional and Network analysis (GENECODIS)
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 (Rodríguez-Martínez et al. 2019, Melero et al. 2016, Ramos et al. 2019)
- Patient stratification and disease classification (Toro-Domínguez et al, 2018)
- Drug discovery and Pharmacogenomics (Toro-Domínguez et al. 2017, Díaz et al. 2016)
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.
– The PRECISESADS project aims to use multi-omics data to establish a classification of systemic autoimmune diseases based on molecular patterns. We are focused on the implementation of state-of-the-art clustering and machine learning methods to establish new disease classification schemas.
– The ONCONET-SUDOE, a cooperation network in oncology, co-financed by the European Interreg Sudoe Programme. In collaboration with Parque Tecnológico de Ciencias de la Salud, we have promoted initiatives such as the Oncothon, a datathon-oriented event to explore the potential of cancer genomics data to open new pathways for cancer diagnosis and treatment.