scholarly journals Decoding the gene coexpression network underlying the ability of Gevuina avellana to live in diverse light conditions

2018 ◽  
Vol 220 (1) ◽  
pp. 278-287 ◽  
Author(s):  
Enrique Ostria‐Gallardo ◽  
Aashish Ranjan ◽  
Yasunori Ichihashi ◽  
Luis J. Corcuera ◽  
Neelima R. Sinha
Keyword(s):  
Coexpression Network ◽  
Gene Coexpression Network ◽  
Light Conditions ◽  
Gene Coexpression ◽  
Gevuina Avellana

scholarly journals Weighted gene coexpression network analysis reveals hub genes involved in cholangiocarcinoma progression and prognosis

2019 ◽  
Vol 49 (10) ◽  
pp. 1195-1206 ◽  
Author(s):  
Aiping Tian ◽  
Ke Pu ◽  
Boxuan Li ◽  
Min Li ◽  
Xiaoguang Liu ◽  
...  
Keyword(s):  
Network Analysis ◽  
Coexpression Network ◽  
Gene Coexpression Network ◽  
Hub Genes ◽  
Gene Coexpression ◽  
Coexpression Network Analysis

scholarly journals Weighted Gene Coexpression Network Analysis Reveals the Dynamic Transcriptome Regulation and Prognostic Biomarkers of Hepatocellular Carcinoma

2020 ◽  
Vol 16 ◽  
pp. 117693432092056
Author(s):  
Shuping Qu ◽  
Qiuyuan Shi ◽  
Jing Xu ◽  
Wanwan Yi ◽  
Hengwei Fan
Keyword(s):  
Hepatocellular Carcinoma ◽  
Differentially Expressed ◽  
Prognostic Biomarkers ◽  
Coexpression Network ◽  
Data Sets ◽  
Independent Data ◽  
Gene Coexpression Network ◽  
Gene Coexpression ◽  
Gene Modules ◽  
Coexpression Network Analysis

This study was aimed at revealing the dynamic regulation of mRNAs, long noncoding RNAs (lncRNAs), and microRNAs (miRNAs) in hepatocellular carcinoma (HCC) and to identify HCC biomarkers capable of predicting prognosis. Differentially expressed mRNAs (DEmRNAs), lncRNAs, and miRNAs were acquired by comparing expression profiles of HCC with normal samples, using an expression data set from The Cancer Genome Atlas. Altered biological functions and pathways in HCC were analyzed by subjecting DEmRNAs to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis. Gene modules significantly associated with disease status were identified by weighted gene coexpression network analysis. An lncRNA-mRNA and an miRNA-mRNA coexpression network were constructed for genes in disease-related modules, followed by the identification of prognostic biomarkers using Kaplan-Meier survival analysis. Differential expression and association with the prognosis of 4 miRNAs were verified in independent data sets. A total of 1220 differentially expressed genes were identified between HCC and normal samples. Differentially expressed mRNAs were significantly enriched in functions and pathways related to “plasma membrane structure,” “sensory perception,” “metabolism,” and “cell proliferation.” Two disease-associated gene modules were identified. Among genes in lncRNA-mRNA and miRNA-mRNA coexpression networks, 9 DEmRNAs and 7 DEmiRNAs were identified to be potential prognostic biomarkers. MIMAT0000102, MIMAT0003882, and MIMAT0004677 were successfully validated in independent data sets. Our results may advance our understanding of molecular mechanisms underlying HCC. The biomarkers may contribute to diagnosis in future clinical practice.

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