|
Abstract:
|
This one-day course will provide a practical introduction to statistical network analysis methods for biological application. The course will cover four classes of methods: statistical methods for network data analysis; inference methods for undirected networks; inference methods for directed networks; and differential network analysis. The methods covered include methods that are widely used in biological applications and, in particular, in the analysis of -omics data, as well as recent developments in statistical machine learning. Throughout, the emphasis will be on practical applications of network analysis methods, as well as their limitations, including validation of results. Case studies using publicly available data will be used to describe various statistical network analysis methods.
The course is based on two short courses taught by the instructors: Since 2012, Dr. Shojaie has taught a short course titled “Pathway and Network Analysis of Omics Data” at the University of Washington. This 2.5-day course has been well received with more than 40 participants in each offering. Dr. Michailidis has taught a 1.5-day short course from 2014-2017 on the statistical analysis of metabolomics data that included a substantial portion on network analysis, and has attracted approximately 50 participants in each offering.
|
