id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-003887-4grjr0h3	McClure, Ryan S.	Unified feature association networks through integration of transcriptomic and proteomic data	2019-09-17		.txt	text/plain	11139	490	49	We show that these networks, including the cross-type edges in the network, are accurate, and we use this approach to interrogate and compare networks inferred from data derived from antibodymediated entry of Dengue virus into cells and from receptor-mediated entry. While a number of the mutual information based methods improved upon PCC in drawing cross-type edges, GENIE3, the random forest method, was by far the best method for creating integrated networks (Fig 2A) . Having shown with our analysis of Dengue virus infection that GENIE3 is the inference method that is best able to create highly integrated and accurate networks of proteomic and transcriptomic data we applied this approach to comparison of networks derived from receptor-mediated Dengue virus infection and antibody-mediated Dengue virus infection. Despite these challenges and the small number of cross-type edges, GENIE3 does emerge as the best method for inferring integrated networks, specifically of proteomic and transcriptomic data.	./cache/cord-003887-4grjr0h3.txt	./txt/cord-003887-4grjr0h3.txt