The group Computational Biology of Tecnun is a multidisciplinary team, with extensive experience in the development of optimization algorithms, statistical analysis, as well as methods based on machine learning and deep learning, mainly focused on issues in the field of human health through data of high molecular resolution (genomics, transcriptomics, proteomics, metabolomics, etc) and instructions of biological data (genomic, pharmacological, metabolic, etc). Currently, we are working on the following topics:

 Metabolic reprogramming in cancer to identify new therapeutic targets and markers of response.

 Integration of massive gene silencing experiments and drugs at framework in precision oncology.

 Study of alternative splicing in different types of cancer: its alterations, causes and effects.

 Predictive models of drug toxicity based on structural features.

 Influence of the gut microbiota on health and nutrition.

 Specific compression schemes for different omics data. Active members in the development of the MPEG-G standard for the representation of genomic data. 

 DNA data analysis. Methods to improve the identification of biological variants in germline and cancer.

 Inference of gene regulatory networks for RNA data from bulk and single-cell sequencing.

 Characterisation of HERV (human endogenous retroviruses) in cancer and brain samples.

During these years, we have actively collaborated with different research centres and companies. The most relevant are: CIMA, Clínica Universidad de Navarra, CIC BioGUNE, Biodonostia, FISABIO, Onkologikoa, University of Granada, Celgene, Biobide, Universitat Politècnica de Catalonia, University of Illinois at Urbana-Champaign, Stanford University, and Universidad de la República (Uruguay).

Members of the group