Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus–Human Protein Interaction Network
Joint Authors
Huang, Tao
Zhang, Yu-Hang
Zeng, Tao
Ding, ShiJian
Chen, Lei
Cai, Yu-Dong
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-7, 7 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-07-09
Country of Publication
Egypt
No. of Pages
7
Main Subjects
Abstract EN
Coronaviruses are specific crown-shaped viruses that were first identified in the 1960s, and three typical examples of the most recent coronavirus disease outbreaks include severe acute respiratory syndrome (SARS), Middle East respiratory syndrome (MERS), and COVID-19.
Particularly, COVID-19 is currently causing a worldwide pandemic, threatening the health of human beings globally.
The identification of viral pathogenic mechanisms is important for further developing effective drugs and targeted clinical treatment methods.
The delayed revelation of viral infectious mechanisms is currently one of the technical obstacles in the prevention and treatment of infectious diseases.
In this study, we proposed a random walk model to identify the potential pathological mechanisms of COVID-19 on a virus–human protein interaction network, and we effectively identified a group of proteins that have already been determined to be potentially important for COVID-19 infection and for similar SARS infections, which help further developing drugs and targeted therapeutic methods against COVID-19.
Moreover, we constructed a standard computational workflow for predicting the pathological biomarkers and related pharmacological targets of infectious diseases.
American Psychological Association (APA)
Zhang, Yu-Hang& Zeng, Tao& Chen, Lei& Ding, ShiJian& Huang, Tao& Cai, Yu-Dong. 2020. Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus–Human Protein Interaction Network. BioMed Research International،Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1133821
Modern Language Association (MLA)
Zhang, Yu-Hang…[et al.]. Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus–Human Protein Interaction Network. BioMed Research International No. 2020 (2020), pp.1-7.
https://search.emarefa.net/detail/BIM-1133821
American Medical Association (AMA)
Zhang, Yu-Hang& Zeng, Tao& Chen, Lei& Ding, ShiJian& Huang, Tao& Cai, Yu-Dong. Identification of COVID-19 Infection-Related Human Genes Based on a Random Walk Model in a Virus–Human Protein Interaction Network. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-7.
https://search.emarefa.net/detail/BIM-1133821
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1133821