Our group is generally interested in contribuing to the development of transformative solutions for biological and biomedical problems by introducing computational, analytical, biomedical, conceptual or technological innovations. Our main focus is on application of Artificial Intelligence to Biomedical Science.
We often rely on integrative frameworks that deploy multiple bio-technologies of different types and scales such as protein-interaction networks, next generation sequencing technology, microarray measurements, genomic and epigenetic analysis, structural and functional genomics, metabolic and regulatory models, prior knowledge, clinical data (EMRs) and sophisticated graph theoretical and probabilistic algorithms aimed to produce meaningful and predictive hypotheses, network models, biomarkers or discoveries that we attempt to validate in the laboratory working with amazing experimental scientists.
Some examples of recent projects include work in Computational and Systems Biology, Bioengineering, Network Signatures of Disease, Functional and Comparative Genomics, Biotechnology, Health-care, Gene Function Prediction.
Computationally we are interested in High Performance Algorithms, Theory, Data mining, Machine Learning and AI.
Most recently we became interested in what we call the Network Biology Axis of Wellness and Disease Prevention and made contributions to a number of basic and translational research questions in diabetes, infectious diseases, health-span, aging, Alzheimer’s, Depression and Cancer.