| Property | Value |
|---|
|
?:abstract
|
-
COVID-19, caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), has quickly become a global health crisis since the first report of infection in December of 2019. However, the infection spectrum of SARS-CoV-2 and its comprehensive protein-level interactions with hosts remain unclear. There is a massive amount of under-utilized data and knowledge about RNA viruses highly relevant to SARS-CoV-2 and their hosts’ proteins. More in-depth and more comprehensive analyses of that knowledge and data can shed new insight into the molecular mechanisms underlying the COVID-19 pandemic and reveal potential risks. In this work, we constructed a multi-layer virus-host interaction network to incorporate these data and knowledge. A machine learning-based method, termed Infection Mechanism and Spectrum Prediction (IMSP), was developed to predict virus-host interactions at both protein and organism levels. Our approach revealed five potential infection targets of SARS-CoV-2, which deserved public health attention, and eight highly possible interactions between SARS-CoV-2 proteins and human proteins. Given a new virus, IMSP can utilize existing knowledge and data about other highly relevant viruses to predict multi-scale interactions between the new virus and potential hosts.
|
|
is
?:annotates
of
|
|
|
?:creator
|
|
|
?:doi
|
-
10.1101/2020.11.09.375394
|
|
?:doi
|
|
|
?:externalLink
|
|
|
?:journal
|
|
|
?:license
|
|
|
?:pdf_json_files
|
-
document_parses/pdf_json/3dee1b2c7705da32139eb1e5b426982154c74292.json
|
|
?:publication_isRelatedTo_Disease
|
|
|
is
?:relation_isRelatedTo_publication
of
|
|
|
?:sha_id
|
|
|
?:source
|
|
|
?:title
|
-
Network-based Virus-Host Interaction Prediction with Application to SARS-CoV-2
|
|
?:type
|
|
|
?:year
|
|
![[This page as RDF]](https://research.tib.eu/covid-19/static/rdf-icon.gif){kind=icon}