id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-012465-tta58o6t	Vlietstra, Wytze J.	Identifying disease trajectories with predicate information from a knowledge graph	2020-08-20		.txt	text/plain	5639	320	49	BACKGROUND: Knowledge graphs can represent the contents of biomedical literature and databases as subject-predicate-object triples, thereby enabling comprehensive analyses that identify e.g. relationships between diseases. Here, we determine whether a sequence of two diseases forms a trajectory by leveraging the predicate information from paths between (disease) proteins in a knowledge graph. To do so, we create four feature sets, based on two methods for representing indirect paths, and both with and without directional information of predicates (i.e., which protein is considered subject and which object). Based on the paths in the knowledge graph, four feature sets are created, based on two methods to represent indirect paths, and both with and without the directional information of predicates was measured with the area under the receiver operator characteristic curve (AUC) of a 10-fold cross-validation experiment [27, 28] .	./cache/cord-012465-tta58o6t.txt	./txt/cord-012465-tta58o6t.txt