Statistics Seminar: Ron Shamir (Tel Aviv University) -- Modularity, classification and networks in analysis of big biomedical data

Abstract:

Abstract: Supervised and unsupervised methods have been used extensively to analyze 
genomics data, with mixed results. On one hand, new insights have led to new 
biological findings. On the other hand, analysis results were often not robust. Here 
we take a look at several such challenges from the perspectives of networks and big 
data. Specifically, we ask if and how the added information from a biological 
network helps in these challenges. We show both examples where the network added 
information is invaluable, and others where it is questionable. We also show that by 
collectively analyzing omic data across multiple studies of many diseases, robustness 
greatly improves.