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Title: Determination of Biomarkers for Diagnosis of Lung Cancer Using Cytoscape-based GO and Pathway Analysis
Lung cancer is the second most common cancer in the world. The aim of this study is to identify biomarkers for lung cancer that can aid in its diagnosis and treatment. The gene expression profiles from GEO database were analyzed by GEO2R to identify Differentially Expressed Genes (DEGs) and further analyzed using Cytoscape. The data was divided into two categories: non-treatment and treatment groups. A total of 407 DEGs (254 upregulated and 153 downregulated) and 259 DEGs (124 upregulated and 135 downregulated) were isolated for non-treatment and treatment studies respectively. The significant Gene Ontologies and pathways enriched with DEGS were identified using Cytoscape apps, BiNGO and ReactomeFIPlugIn, respectively. Hub genes based on network parameters - Degree, Closeness and Betweenness - were isolated using CytoHubba. In conclusion, DEGs identified in this study may play an important role in early diagnosis or as biomarkers of lung cancer.
Authors:
; ; ;
Award ID(s):
1901628 1651917
Publication Date:
NSF-PAR ID:
10141528
Journal Name:
The 20th International Conference on Bioinformatics and Computational Biology
Page Range or eLocation-ID:
17-23
Sponsoring Org:
National Science Foundation
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