Bioinformatics and Health Data Science

Omics technologies enable the simultaneous quantification of thousands of biological variables, generating large volumes of data. This wealth of information necessitates the use of advanced analytical techniques to manage and extract meaningful knowledge from these extensive datasets. Our primary research focus is on developing and applying novel computational and statistical methods for the integration and analysis of multi-omics and biomedical data, aiming to enhance our understanding of the molecular mechanisms underlying complex diseases and to advance their diagnosis and treatment. Specifically, we concentrate on the following research areas:

Methods for Integrated Analysis of Biomedical Data

The rapid growth of omics techniques has resulted in an explosion of data available in public repositories, offering an invaluable resource for generating new knowledge and hypotheses. Within our group, we develop innovative methods and software tools for data integration, with a particular emphasis on multi-omics data fusion.
Our primary goal is to establish molecular signatures for patient classification and to create predictive models that assist in forecasting treatment responses or prognoses in complex pathologies. This work also incorporates information from electronic medical records. In this context, we actively collaborate with other research groups specializing in autoimmune diseases and cancer.

Development of Software and Bioinformatic Analysis Tools

One of our key objectives is to develop open-source applications that make our methodologies accessible to the scientific community. These applications include tools for data integration and functional analysis, which are widely utilized by researchers worldwide. A complete list of the software we have developed is available at https://compbio.ugr.es/tools/.