Computational Biomedicine

The advance of high-throughput technologies, the increase in biological and clinical knowledge, and the potential of computational approaches provide an exciting research scenario for the generation of new and useful biomedical knowledge. Within this scientific framework, we are working on the following lines of research:

1. Improving the understanding of molecular mechanisms in neuronal pathologies: a) Generation of single-cell atlases to decipher sex differences in neurodegenerative diseases (Parkinson’s disease, Alzheimer’s disease and multiple sclerosis); b) Identification of biological pathways in behavioural alteration pathologies (schizophrenia and autism spectrum disorder); c) Detection of transcriptomic signatures for the understanding of molecular mechanisms associated with spinal cord injury; d) Study of differential sex profiles in neuroinflammation associated with alcohol use disorders, through integrative multi-omics strategies.
2. Finding novel biomarkers in cancer: a) Development and application of big-data analysis methods for the identification of novel diagnostic and progression biomarkers in cancer studies; b) Neurobiology of cancer: description of the role of the nervous system in oncological diseases and identification of possible clinical implications in oncology. Identifying transcriptomic signatures shared between neurodegenerative diseases and brain metastatic melanoma.
3. Clinical targets and predictors in metabolic disorders: a) Detection of potential clinical targets in obesity, diabetes and MAFLD (metabolic associated fatty liver disease) through massive analysis of omics data; b) Clinical predictors based on high-throughput technologies and artificial intelligence methods.