About: 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

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About: 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 Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has 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
Creator	Niu, Gang Zhang, Zhonghai Ji, Xiaoyang Tan, Guangming Xue, Yiqing Zhai, Yubo Zhang, Chunli Zhang, Chunming
Source	BioRxiv; MedRxiv
abstract	Faced with the current large-scale public health emergency, collecting, sorting, and analyzing biomedical information related to the “coronavirus” should be done as quickly as possible to gain a global perspective, which is a basic requirement for strengthening epidemic control capacity. However, for human researchers studying the viruses and the hosts, the vast amount of information available cannot be processed effectively and in a timely manner, particularly when the scientific understanding may be limited, which can further lower the information processing efficiency. We present TWIRLS, a method that can automatically acquire, organize, and classify information. Additionally, independent functional data sources can be added to build an inference system using a machine-based approach, which can provide relevant knowledge to help human researchers quickly establish subject cognition and to make more effective decisions. TWIRLS can automatically analyze more than three million words in more than 14,000 literature articles in only 4 hours. Combining with generalized gene interaction databases creates a data interface that can help researchers to further analyze the information. Using the TWIRLS system, we found that an important regulatory factor angiotensin-converting enzyme 2 (ACE2) may be involved in the host pathological changes on binding to the coronavirus after infection. After triggering functional changes in ACE2/AT2R, an imbalance in the steady-state cytokine regulatory axis involving the Renin-Angiotensin System and IP-10 leads to a cytokine storm.
has issue date	2020-03-02(xsd:dateTime)
bibo:doi	10.1101/2020.02.27.967588
has license	biorxiv
sha1sum (hex)	0e26cd0574660dda25ba4f1cf70d30744fbaaceb
schema:url	https://doi.org/10.1101/2020.02.27.967588
resource representing a document's 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
schema:publication	bioRxiv
resource representing a document's body	covid:0e26cd0574660dda25ba4f1cf70d30744fbaaceb#body_text
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