Study on pathological mechanism of pneumonia infected by coronavirus based on time-series gene co-expression network analysis
9th IEEE International Conference on Bioinformatics and Computational Biology, ICBCB 2021
; : 168-173, 2021.
Article
in English
| Scopus | ID: covidwho-1402792
ABSTRACT
Recently, the epidemic of COVID-19 infection broke out in Wuhan, China. To explore the pathological mechanism of pneumonia infected by coronavirus, we built a bioinformatics pipeline based on time-series gene co-expression network analysis to analyze the gene expression profile of lung cells in mice infected by SARS-Cov (GSE19137). In this study, Pearson correlation analysis was performed to construct a gene co-expression network. Time-ordered gene network modules were digged out by BFS algorithm. PageRank algorithm was used to explore HUB genes related to pneumonia infected by coronavirus. Based on the information we got, we think that cell lines infected by coronavirus might go through 5 stages, and 10 HUB genes(AKT1, CD68, CTSS, FCGR3A, HSPA8, PTPRC, UBC, VCP, PRPF31, ITPKB) might play a key role in coronavirus infection. This might provide some hints for coronavirus related research. © 2021 IEEE.
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Collection:
Databases of international organizations
Database:
Scopus
Type of study:
Experimental Studies
Language:
English
Journal:
9th IEEE International Conference on Bioinformatics and Computational Biology, ICBCB 2021
Year:
2021
Document Type:
Article
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