Causal Analysis of
Biomedical Data
A key goal of biomedical data science is to understand cause and effect in disease processes using mechanistic modelling and causal inference approaches. In this lecture series, you will learn how mechanistic modelling and causal inference can help interpret disease processes at the molecular, cellular and systemic levels. This series brings together global experts in causal inference, computational biology and metabolic modelling to discuss mechanistic omics analysis, personalised medicine and public health applications.
Upcoming lectures
‟ Join us in exploring the fast-evolving field of causal analysis of
biomedical data and connect with international experts!”
Assistant professor in Machine Learning and Bioinformatics and Principal Investigator of the Biomedical Data Science group at the Luxembourg Centre for Systems Biomedicine
The Causal Analysis of Biomedical Data Lecture Series is supported by the Luxembourg National Research Fund (FNR) RESCOM Program (RESCOM24/18799474/LS_CasualBio).
