General Information

Omics technologies and new experimental techniques allow the simultaneous quantification of thousands of biological variables and generate large volumes of data. This amount of information necessitates the use of appropriate analysis techniques to handle and extract knowledge from these massive datasets. Our main research lines focus on developing and applying new computational and statistical methods for the integration and analysis of multi-omics and biomedical data, aiming to achieve a better understanding of the molecular mechanisms associated with complex diseases, as well as advancing their diagnosis and treatment. Specifically, we are interested in developing applications and methodologies in
different contexts:

Methods for integrated analysis of multi-omics data

The growth of omics techniques has led to an explosion in the availability of data in public repositories. With the appropriate methodologies, this data is an invaluable source for generating new knowledge, hypotheses, and predictive models. In our group, we have developed new methods and software based on meta-analysis techniques and data integration, applied to biomarker discovery and functional annotation analysis,among other fields.

Development of computational techniques to establish molecular signatures and prediction models for drug response and patient classification

We are creating algorithms to establish omics signatures that define new classification models and guide in predicting responses to treatments or prognosis of pathologies, also integrating information from electronic medical records. In this context, we have various collaborations with other expert groups in different pathologies such as autoimmune diseases and cancer.

Development of software and bioinformatic analysis tools

One of our objectives is also to develop open-source applications that make our methodologies available to the scientific community. These applications are widely used for analyzing biomedical data. The list of developed software is available at https://compbio.ugr.es/tools/.

Social Impact

Our research has a highly multidisciplinary component, allowing us to establish synergies with other groups that have resulted in patents and joint projects with a clear translational focus. Some of our methodologies have also been implemented in open-source software packages, which are globally used by research groups to extract information from biomedical data and generate new knowledge in diverse areas.

Activities to Strengthen the Strategic Research Line

We actively participate in different bioinformatics networks and consortia that enhance the center’s national and international visibility in these areas, such as TransBionet (Translational Bioinformatics Network) in which Dr. Pedro Carmona has been coIP in the “Redes de Excelencia” projects. We promote engagement in collaborative projects with other groups to address complex challenges with a strong inter- and multidisciplinary science component. We are committed to maintaining high criteria of excellence and quality in our publications, aligned with the center, with a percentage > 85% in Q1.

Internationalization

We are part of a working group to apply for an ERC Synergy grant (we have already participated in the last call, and although our proposal has not been granted, we have reinforced the research proposal for future calls). We have consolidated collaborations with different international groups, such as Dr. Julio Sáez (Head of research at EBI_EMBL) or Dr. Giusepe Jurgan (Head of Data Science for Health Unit), with joint projects and mobility of students (predoct and postdoc). We plan to launch proposals for Marie Curie actions and COST.

Members

Principal Investigator - R4

Pedro Carmona

Researchers - R3

Manuela Expósito Ruiz

Postdoctoral Researchers - R2

Jordi Matorell

Predoctoral Researchers - R1

Marina Vargas

Samuel Pérez Fernández

Pablo Pedro Jurado Bascón

Projects
Publications