Identification of macrophage-related candidate genes in lupus nephritis using bioinformatics analysis

2018 ◽  
Vol 46 ◽  
pp. 43-51 ◽  
Author(s):  
Bingyan Shu ◽  
Yi Fang ◽  
Weichun He ◽  
Junwei Yang ◽  
Chunsun Dai
Keyword(s):  
Lupus Nephritis ◽  
Candidate Genes ◽  
Bioinformatics Analysis

scholarly journals Gene Expression Profiling of Type 2 Diabetes Mellitus by Bioinformatics Analysis

2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Huijing Zhu ◽  
Xin Zhu ◽  
Yuhong Liu ◽  
Fusong Jiang ◽  
Miao Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Diabetes Mellitus ◽  
Type 2 Diabetes ◽  
Candidate Genes ◽  
Signaling Pathway ◽  
Bioinformatics Analysis ◽  
Kegg Pathway ◽  
Ppi Network ◽  
Kegg Pathway Analysis

Objective. The aim of this study was to identify the candidate genes in type 2 diabetes mellitus (T2DM) and explore their potential mechanisms. Methods. The gene expression profile GSE26168 was downloaded from the Gene Expression Omnibus (GEO) database. The online tool GEO2R was used to obtain differentially expressed genes (DEGs). Gene Ontology (GO) term enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were performed by using Metascape for annotation, visualization, and comprehensive discovery. The protein-protein interaction (PPI) network of DEGs was constructed by using Cytoscape software to find the candidate genes and key pathways. Results. A total of 981 DEGs were found in T2DM, including 301 upregulated genes and 680 downregulated genes. GO analyses from Metascape revealed that DEGs were significantly enriched in cell differentiation, cell adhesion, intracellular signal transduction, and regulation of protein kinase activity. KEGG pathway analysis revealed that DEGs were mainly enriched in the cAMP signaling pathway, Rap1 signaling pathway, regulation of lipolysis in adipocytes, PI3K-Akt signaling pathway, MAPK signaling pathway, and so on. On the basis of the PPI network of the DEGs, the following 6 candidate genes were identified: PIK3R1, RAC1, GNG3, GNAI1, CDC42, and ITGB1. Conclusion. Our data provide a comprehensive bioinformatics analysis of genes, functions, and pathways, which may be related to the pathogenesis of T2DM.

scholarly journals Identification of Candidate Genes and Pathways in Dexmedetomidine-Induced Cardioprotection in the Rat Heart by Bioinformatics Analysis

2019 ◽  
Vol 20 (7) ◽  
pp. 1614 ◽  
Author(s):  
Yusuke Yoshikawa ◽  
Naoyuki Hirata ◽  
Hirofumi Terada ◽  
Yasuaki Sawashita ◽  
Michiaki Yamakage
Keyword(s):  
Map Kinase ◽  
Candidate Genes ◽  
Phosphatase Activity ◽  
Bioinformatics Analysis ◽  
Ischemia Reperfusion ◽  
Differentially Expressed ◽  
P53 Pathway ◽  
Rat Hearts ◽  
Significant Pathway ◽  
Adrenergic Receptor Agonist

Dexmedetomidine (DEX), a highly selective alpha2 adrenergic receptor agonist, directly protects hearts against ischemia/reperfusion (I/R) injury. However, the detailed mechanism has not been fully elucidated. We studied differentially expressed mRNAs and miRNAs after DEX administration in rat hearts by comprehensive analysis. Additionally, bioinformatics analysis was applied to explore candidate genes and pathways that might play important roles in DEX-induced cardioprotection. The results of microarray analysis showed that 165 mRNAs and 6 miRNAs were differentially expressed after DEX administration. Through bioinformatics analysis using differentially expressed mRNAs, gene ontology (GO) terms including MAP kinase tyrosine/serine/threonine phosphatase activity and pathways including the p53 pathway were significantly enriched in the down-regulated mRNAs. Dusp1 and Atm were associated with the GO term of MAP kinase tyrosine/serine/threonine phosphatase activity and the p53 pathway, respectively. On the other hand, no significant pathway was found in the target mRNAs of deregulated miRNAs. The results indicated some possible key genes and pathways that seem to be of significance in DEX-induced cardioprotection, although miRNAs seem to be unlikely to contribute to cardioprotection induced by DEX.

scholarly journals Identification of Candidate Genes for Osteoporosis via Integrated Bioinformatics Analysis

2021 ◽  
Vol 83 ◽  
Author(s):  
Huan Xin Xie ◽  
Lei Cao ◽  
Lin Lin Ye ◽  
G. X. Shan ◽  
C. J. Jiang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Bioinformatics Analysis

scholarly journals Identification of key candidate genes in local dorsal root ganglion inflammation by integrated bioinformatics analysis

2021 ◽  
Vol 22 (2) ◽  
Author(s):  
Linhai Chen ◽  
Junshui Zheng ◽  
Zhuan Yang ◽  
Weiwei Chen ◽  
Yangjian Wang ◽  
...  
Keyword(s):  
Dorsal Root Ganglion ◽  
Candidate Genes ◽  
Dorsal Root ◽  
Bioinformatics Analysis
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