Bioinformatics analysis of gene expression profiles of Inclusion body myositis

2020 ◽  
Vol 91 (6) ◽  
Author(s):  
Jiuchang Zhang ◽  
Elona Khasanova ◽  
Liming Zhang
Keyword(s):  
Gene Expression ◽  
Inclusion Body ◽  
Inclusion Body Myositis ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Bioinformatics Analysis of Gene Expression Profiles for Risk Prediction in Patients with Septic Shock

2019 ◽  
Vol 25 ◽  
pp. 9563-9571 ◽  
Author(s):  
Yingchun Hu ◽  
Lingxia Cheng ◽  
Wu Zhong ◽  
Muhu Chen ◽  
Qian Zhang
Keyword(s):  
Gene Expression ◽  
Septic Shock ◽  
Risk Prediction ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles

scholarly journals Identify key genes and pathways in pancreatic ductal adenocarcinoma via bioinformatics analysis

2020 ◽  
Author(s):  
Huatian Luo ◽  
Da-qiu Chen ◽  
Jing-jing Pan ◽  
Zhang-wei Wu ◽  
Can Yang ◽  
...  
Keyword(s):  
Gene Expression ◽  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Gene Expression Omnibus ◽  
Ductal Adenocarcinoma ◽  
Hub Genes ◽  
Expression Levels

Abstract Background: Pancreatic cancer has many pathologic types, among which pancreatic ductal adenocarcinoma (PDAC) is the most common one. Bioinformatics has become a very common tool for the selection of potentially pathogenic genes. Methods: Three data sets containing the gene expression profiles of PDAC were downloaded from the gene expression omnibus (GEO) database. The limma package of R language was utilized to explore the differentially expressed genes (DEGs). To analyze functions and signaling pathways, the Database Visualization and Integrated Discovery (DAVID) was used. To visualize the protein-protein interaction (PPI) of the DEGs ,Cytoscape was performed under the utilization of Search Tool for the Retrieval of Interacting Genes (STRING). With the usage of the plug-in cytoHubba in cytoscape software, the hub genes were found out. To verify the expression levels of hub genes, Gene Expression Profiling Interactive Analysis (GEPIA) was performed. Last but not least, UALCAN analysis online tool was implemented to analyze the overall survival. Results: The 376 DEGs were highly enriched in biological processes including signal transduction, apoptotic process and several pathways, mainly associated with Protein digestion and absorption and Pancreatic secretion pathway. The expression levels of nucleolar and spindle associated protein 1 (NUSAP1) and SHC binding and spindle associated 1 (SHCBP1) were discovered highly expressed in pancreatic ductal adenocarcinoma tissues. NUSAP1 and SHCBP1 had a high correlation with prognosis. Conclusions: The findings of this bioinformatics analysis indicate that NUSAP1 and SHCBP1 may be key factors in the prognosis and treatment of pancreatic cancer.

Bioinformatics analysis of gene expression profiles in childhood B-precursor acute lymphoblastic leukemia

Hematology ◽  
2014 ◽  
Vol 20 (7) ◽  
pp. 377-383 ◽  
Author(s):  
Jun Li ◽  
Xiaowen Zhai ◽  
Hongsheng Wang ◽  
Xiaowen Qian ◽  
Hui Miao ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Lymphoblastic Leukemia ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Lymphoblastic Leukemia ◽  
Gene Expression Profiles

scholarly journals Systemic bioinformatics analysis of recurrent aphthous stomatitis gene expression profiles

Oncotarget ◽  
2017 ◽  
Vol 8 (67) ◽  
pp. 111064-111072 ◽  
Author(s):  
Jian Wu ◽  
Zheng-Ping Chen ◽  
An-Quan Shang ◽  
Wei-Wei Wang ◽  
Zong-Ning Chen ◽  
...  
Keyword(s):  
Gene Expression ◽  
Bioinformatics Analysis ◽  
Expression Profiles ◽  
Gene Expression Profiles ◽  
Recurrent Aphthous Stomatitis ◽  
Aphthous Stomatitis
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