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Multimodal Data Integration in Digital Health for Rare Genetic Diseases

The technological advances and accumulation of biomedical datasets are yielding unprecedented opportunities to better understand human diseases. However, translating massive and heterogeneous data into knowledge necessitates proper exploration and integration tools. The talk will focus on different computational strategies for the integration of heterogeneous datasets.  I will describe multilayer networks that incorporate different sources of biomedical interactions, as well as associated network exploration algorithms. I will also mention joint dimensionality reduction to extract biological knowledge simultaneously from multiple omics or modalities. On the application side, I will discuss the application of these different algorithms in the context of the analysis of rare genetic diseases, which raise various challenges: many patients are undiagnosed, phenotypes can be highly heterogeneous, and only a few treatments exist.

About the speaker

Anaïs Baudot is CNRS research director of the Networks and Systems Biology for Diseases Group she founded at the Marseille Medical Genetics (MMG) Unit in 2018. Her main interests are developing Artificial Intelligence and digital approaches to extract knowledge from multimodal biological data and studying human genetic diseases. She earned her PhD in Bioinformatics at the Developmental Biology Institute from the Aix-Marseille University in 2007.  She did a postdoc in the laboratory of Prof. Alfonso Valencia in the Spanish National Cancer Research Centre in Madrid, Spain. After that, she was recruited by the CNRS in 2010, where she worked at the Marseille Mathematics Institute before the funding of her own group at the MMG.

This lecture series is organised jointly by the Luxembourg Centre of Systems Biomedicine (LCSB) at the University of Luxembourg and the Luxembourg Institute of Health (LIH) with financial support from the National Research Fund (FNR).