Author: Xiaoyang Ji; Chunming Zhang; Yubo Zhai; Zhonghai Zhang; Yiqing Xue; Chunli Zhang; Guangming Tan; Gang Niu
Title: TWIRLS, an automated topic-wise inference method based on massive literature, suggests a possible mechanism via ACE2 for the pathological changes in the human host after coronavirus infection Document date: 2020_2_26
ID: f21dknmb_10
Snippet: TWIRLS first calculated the specific co-distribution between CSHGs in local samples, then determined the distance between each pair of CSSEs and performs dichotomy clustering according to the linkage relationship between CSSEs and CSHGs. This classified the 623 entities into 32 categories represented as C0-C31 (see category number in Table S1 , Sheet 1 second column). In addition, for each category, TWIRLS also cited the top ten most relevant ref.....
Document: TWIRLS first calculated the specific co-distribution between CSHGs in local samples, then determined the distance between each pair of CSSEs and performs dichotomy clustering according to the linkage relationship between CSSEs and CSHGs. This classified the 623 entities into 32 categories represented as C0-C31 (see category number in Table S1 , Sheet 1 second column). In addition, for each category, TWIRLS also cited the top ten most relevant references for human researchers (Table S2) . Therefore, in any category, according to the CSSE and the most relevant literature, we can quickly provide "Labels of conclusion-drawn-by-human-researcher" (HR Labels) for this category. This label outlines the most relevant research directions of the current entity category. For example, for category C3, the HR label is "Neurotrophic Coronavirus Related to Immune-Mediated Demyelination". We have summarized the HR labels for the 32 entity categories in Table 1 .
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