About: Coronavirus-Human protein-protein interaction network

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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	Coronavirus-Human protein-protein interaction network
Creator	Naghibzadeh, Mahmoud Savadi, Abdorreza Abdorreza, Abdorreza Babak, Babak Khorsand, Babak Khorsand, Khorsand Savadi, Savadi
Source	Elsevier; Medline; PMC
abstract	Abstract SARS-CoV-2 is the novel coronavirus which caused the COVID-19 pandemic and infected more than 10 million victims and resulted in over 500,000 deaths in 213 countries around the world. Having no symptoms in the first week of infection increases the rate of spreading virus. This increasing rate and consequently increasing number of infected individuals necessitate an immediate development of proper diagnostic methods and effective treatments. To date, no specific treatment is detected for curing COVID-19. SARS-CoV-2, similar to other viruses, needs to interact with the host proteins to reach the host and replicate its genome. Accordingly, host-virus protein-protein interactions’ (PPI) identification could be useful in predicting the behavior of virus and designing antiviral drugs. Identification of host-virus PPIs with experimental approaches are so time consumable, and so computational approaches are usually applied. In this study, we developed a new method to predict SARS-CoV-2-human PPIs. Our model is a three-layer network in which the first layer contains the most similar Alphainfluenzavirus proteins to SARS-CoV-2 proteins. The second layer contains protein-protein interactions between Alphainfluenzavirus proteins and human proteins. The third layer reveals protein-protein interactions between SARS-CoV-2 proteins and human proteins by using the clustering coefficient network property on the two first layers. For further analysis on the results of our prediction network, we investigated human proteins targeted by SARS-CoV-2 proteins and report the most central human proteins in human PPI network. Moreover, differentially expressed genes of two available GSE were investigated and PPIs of SARS-CoV-2-human network, the human proteins of which were related to upregulated genes, were reported.
has issue date	2020-08-13(xsd:dateTime)
bibo:doi	10.1016/j.imu.2020.100413
bibo:pmid	32838020
has license	els-covid
sha1sum (hex)	1f467ed4a521d92390ea14a408217a6068826a3a
schema:url	https://doi.org/10.1016/j.imu.2020.100413
resource representing a document's title	Coronavirus-Human protein-protein interaction network
has PubMed Central identifier	PMC7425553
has PubMed identifier	32838020
schema:publication	Informatics in medicine unlocked
resource representing a document's body	covid:1f467ed4a521d92390ea14a408217a6068826a3a#body_text
is schema:about of	named entity 'predict' named entity 'interactions' named entity 'time' named entity 'betweenness' named entity 'protein-protein interactions' named entity 'predicting' named entity 'upregulated' named entity 'proteins' named entity 'number' named entity 'proteins' named entity 'interaction' named entity 'NEW' named entity 'SPREADING' named entity 'REVEALS' named entity 'OUR' named entity 'METHOD' named entity 'WEEK' named entity 'proteins' named entity 'proteins' named entity 'prediction' named entity 'layer' named entity 'effective' named entity 'SARS-CoV-2' named entity 'Alphainfluenzavirus' named entity 'SARS-CoV-2' named entity 'human' named entity 'SARS-CoV-2' named entity 'behavior' named entity 'Alphainfluenzavirus' named entity 'host-pathogen' named entity 'protein' named entity 'SARS-CoV-2' named entity 'protein interaction' named entity 'betweenness' named entity 'virus' named entity 'upregulated' named entity 'viruses' named entity 'proteins' named entity 'network topology' named entity 'Figure 8' named entity 'ASA' named entity 'quantile' named entity 'protein' named entity 'ASA' named entity 'genome' named entity 'Gene ontology' named entity 'MERS-CoV' named entity 'secondary structure' named entity 'similarity matrix' named entity 'Alphainfluenzavirus' named entity 'Gene ontology' named entity 'Molecular function' named entity 'bipartite graph' named entity 'SARS-CoV-2' named entity 'NEDD8' named entity 'exponential rate' named entity 'world health organization' named entity 'long time' named entity 'IAV' named entity 'Longest common substring' named entity 'SARS-CoV' named entity 'Gene ontology' named entity 'common cold' named entity 'ASA' named entity 'MERS-CoV' named entity 'Primary structure' named entity 'ortholog' named entity 'virus' named entity 'ortholog' named entity 'lack the capacity' named entity 'cytosine' named entity 'Sarbecovirus' named entity 'SARS-CoV-2' named entity 'minks' named entity 'Betacoronavirus'

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