id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-335538-thd5oaef	Ji, Xiaoyang	TWIRLS, a knowledge‐mining technology, suggests a possible mechanism for the pathological changes in the human host after coronavirus infection via ACE2	2020-07-13		.txt	text/plain	5274	252	46	First, TWIRLS can process and summarize the massive biomedical literature on coronaviruses, and then collect, classify, and analyze reported coronavirus studies to reveal host-related entities based on the distribution of specific genes in the text of the articles. We obtained text data (referred to as the local samples) from all related peer reviewed articles published by human researchers that contained the keyword "coronavirus" including the title, abstracts, and author and affiliation information (total 3,182,687 words). TWIRLS first calculates the specific co-distribution between CSHGs in local samples, then determines the distance between each pair of CSSEs and performs dichotomy clustering according to the linkage relationship between CSSEs and CSHGs. This step classified the 623 entities into 32 categories represented as C0-C31 (see category number in Table S1 , Sheet 1 second column). Interestingly, CSHGs in the 2 connections of ACE2 and DPP4 associated with category C5 were also enriched in category C3, inferring that the information summarized in category C3 probably describes the underlying mechanisms of the pathological changes after coronavirus infection.	./cache/cord-335538-thd5oaef.txt	./txt/cord-335538-thd5oaef.txt