Colorado State University
Title: Pathway Expression Analysis
Short Abstract: This project introduces a pathway expression framework as an approach for constructing derived biomarkers. The pathway expression framework incorporates the biological connections of genes leading to a biologically relevant model. Using this framework, we distinguish between shedding subjects post-infection and all subjects pre-infection in human blood transcriptomic samples challenged with various respiratory viruses: H1N1, H3N2, HRV (Human Rhinoviruses), and RSV (Respiratory Syncytial Virus). Additionally, pathway expression data is used for selecting discriminatory pathways from these experiments. The classification results and selected pathways are benchmarked against standard gene expression based classification and pathway ranking methodologies. We find that using the pathway expression data along with selected pathways, which have minimal overlap with high ranking pathways found by traditional methods, improves balanced success rates across experiments.
Presenter Biosketch: Nathan Mankovich is a 5th year graduate student in the department of mathematics at Colorado State University.
Link to Full Abstract: Mankovich_Nathan
Link to Poster: Poster nathan mankovich