Himmelstein DS, Lizee A, Hessler C, Brueggeman L, Chen SL, Hadley D, Green A, Khankhanian P, Baranzini SE (2017) Systematic integration of biomedical knowledge prioritizes drugs for repurposing. eLife doi:10.7554/eLife.26726
Himmelstein DS, Baranzini SE (2015) Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes. PLOS Computational Biology doi:10.1371/journal.pcbi.1004259
Title: Heterogeneous Network Visualization with Cytoscape: An Integrative Approach to the Genetics of Complex Human Disease
Description: To provide context for understanding disease-gene associations, we integrated public resources into a heterogeneous network. The network contains 40,343 nodes (across 18 types) and 1,608,168 edges (across 19 types). Using the network's topology, we learned influential mechanisms underlying pathogenesis and predicted the probability that each gene was associated with each disease.
A short video describing the use of HNEP for predicting disease-associated genes.