Wasserstein distance

Network-based clustering approaches for integrative multiomics data and drug response prediction

Zehor Belkhatir, Senior Lecturer, Control Engineering, De Montfort University

Sep 20, 15:00 - 16:00

B1 L2 H2

multiomics data integration Wasserstein distance gene ontology

Biological data sets, such as gene expressions, copy number alteration, and pharmacogenomics, are often high-dimensional and thus difficult to analyze and interpret. This talk presents two data analysis methodologies that we recently developed based on network analysis via Wasserstein optimal transport combined with unsupervised classification techniques.