Results 11 to 20 of about 148,880 (283)

Weighted Gene Co-Expression Network Analysis of Oxymatrine in Psoriasis Treatment

Journal of Inflammation Research, 2023
Xiaoxiao Xue,1 Yatao Guo,2 Qianying Zhao,3 Yongwen Li,1 Mi Rao,1 Wenjing Qi,1 Huijuan Shi1 1Department of Dermatovenereology, the General Hospital of Ningxia Medical University, Yinchuan, 750004, People’s Republic of China; 2Dermatological Department ...
Xue X, Guo Y, Zhao Q, Li Y, Rao M, Qi W, Shi H   +6 more
doaj   +3 more sources

Three-gene prognostic biomarkers for seminoma identified by weighted gene co-expression network analysis.

PLoS ONE, 2020
Testicular germ cell tumors (TGCTs) are common in young males, and seminoma accounts for a large proportion of TGCTs. However, there are limited records on the exploration of novel biomarkers for seminoma.
Hualin Chen, Gang Chen, Yang Pan, Xiaoxiang Jin   +3 more
doaj   +3 more sources

Identification of glioblastoma gene prognosis modules based on weighted gene co-expression network analysis

BMC Medical Genomics, 2018
Background Glioblastoma multiforme, the most prevalent and aggressive brain tumour, has a poor prognosis. The molecular mechanisms underlying gliomagenesis remain poorly understood.
Pengfei Xu, Jian Yang, Junhui Liu, Xue Yang, Jianming Liao, Fanen Yuan, Yang Xu, Baohui Liu, Qianxue Chen   +8 more
doaj   +3 more sources

Weighted gene co-expression network analysis of hub genes in lung adenocarcinoma [PDF]

Evolutionary Bioinformatics, 2021
Lung adenocarcinoma (LUAD) is a tumor with high incidence. This study aimed to identify the central genes of LUAD. LUAD were analyzed by weighted gene co-expression network (WGCNA), and differentially expressed genes (DEGs) were identified. Samples were obtained from The Cancer Genome Atlas (TCGA) and Genotype Tissue Expression (GTEx) databases and ...
Xuan Luo, Lei Feng, WenBo Xu, XueJing Bai, MengNa Wu   +4 more
openaire   +3 more sources

Predicting glioblastoma prognosis networks using weighted gene co-expression network analysis on TCGA data [PDF]

BMC Bioinformatics, 2012
Background Using gene co-expression analysis, researchers were able to predict clusters of genes with consistent functions that are relevant to cancer development and prognosis.
Xiang Yang, Zhang Cun-Quan, Huang Kun
doaj   +3 more sources

PyWGCNA: a Python package for weighted gene co-expression network analysis

Bioinformatics, 2022
Abstract Motivation Weighted gene co-expression network analysis (WGCNA) is frequently used to identify modules of genes that are co-expressed across many RNA-seq samples. However, the current R implementation is slow, is not designed to compare modules between multiple WGCNA networks, and its ...
Narges Rezaie, Fairlie Reese, Ali Mortazavi   +2 more
openaire   +4 more sources

Identification of key gene modules and genes in colorectal cancer by co-expression analysis weighted gene co-expression network analysis [PDF]

Bioscience Reports, 2020
Abstract Colorectal cancer (CRC) has been one of the most common malignancies worldwide, which tends to get worse for the growth and aging of the population and westernized lifestyle. However, there is no effective treatment due to the complexity of its etiology. Hence, the pathogenic mechanisms remain to be clearly defined.
Peng Wang, Huaixin Zheng, Jiayu Zhang, Yashu Wang, Pingping Liu, Xiaoyan Xuan, Qianru Li, Ying Du   +7 more
openaire   +2 more sources

Weighted Gene Co-expression Network Analysis Identifies Crucial Genes Mediating Progression of Carotid Plaque [PDF]

Frontiers in Physiology, 2021
BackgroundSurface rupture of carotid plaque can cause severe cerebrovascular disease, including transient ischemic attack and stroke. The aim of this study was to elucidate the molecular mechanism governing carotid plaque progression and to provide candidate treatment targets for carotid atherosclerosis.MethodsThe microarray dataset GSE28829 and the ...
Mengyin Chen, Siliang Chen, Dan Yang, Jiawei Zhou, Bao Liu, Yuexin Chen, Wei Ye, Hui Zhang, Lei Ji, Yuehong Zheng   +9 more
openaire   +3 more sources

Distance correlation application to gene co-expression network analysis

BMC Bioinformatics, 2022
Background To construct gene co-expression networks, it is necessary to evaluate the correlation between different gene expression profiles. However, commonly used correlation metrics, including both linear (such as Pearson’s correlation) and monotonic ...
Jie Hou, Xiufen Ye, Weixing Feng, Qiaosheng Zhang, Yatong Han, Yusong Liu, Yu Li, Yufen Wei   +7 more
doaj   +1 more source

Identify the signature genes for diagnose of uveal melanoma by weight gene co-expression network analysis [PDF]

International Journal of Ophthalmology, 2015
AIM: To identify and understand the relationship between co-expression pattern and clinic traits in uveal melanoma, weighted gene co-expression network analysis (WGCNA) is applied to investigate the gene expression levels and patient clinic features ...
Kai Shi, Zhi-Tong Bing, Gui-Qun Cao, Ling Guo, Ya-Na Cao, Hai-Ou Jiang, Mei-Xia Zhang   +6 more
doaj   +1 more source