id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-271693-7tg21up3	Zheng, Fan	Identifying persistent structures in multiscale ‘omics data	2020-10-03		.txt	text/plain	4889	291	48	Many different approaches have been devised or applied to detect structures in biological data, including standard clustering, network community detection, and low-dimensional data projection [5] [6] [7] , some of which can be tuned for sensitivity to objects of a certain size or scale (so-called 'resolution parameters') [8, 9] . We first explored the idea of measuring community persistence via analysis of synthetic datasets [15] in which communities were simulated and embedded in the similarity network at two different scales (Supplementary Fig. 1a; Methods) . Application to protein-protein interaction networks from budding yeast and human found that HiDeF captured knowledge in GO more significantly than previous pipelines proposed for this task, including the NeXO approach to hierarchical community detection [23] and standard hierarchical clustering of pairwise protein distances calculated by three recent network embedding approaches [24] [25] [26] (Fig. 3a, Fig. 7) .	./cache/cord-271693-7tg21up3.txt	./txt/cord-271693-7tg21up3.txt