Laboratory of Multi-omic Integrative Bioinformatics

Modern life science research is a highly multidisciplinary endeavor often requiring the joint analysis of highly heterogeneous data sources, such as large-scale single-cell multi-omics datasets, structured ontology-driven annotations, unstructured published literature and imaging data. Using a holistic approach, one can often detect patterns which provide deeper insights into the biological and/or pathophysiological processes under study. However, such data analysis approaches are complex when dealing with heterogeneous and highly dimensional datasets. By leveraging breakthrough advances in the fields of artificial intelligence and statistical modelling, our group aims to develop novel computational methodologies for data fusion and pattern recognition and apply them to further our understanding of human disease.