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2020-06-24
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Table9_LGALS1 was related to the prognosis of clear cell renal cell carcinoma identified by weighted correlation gene network analysis combined with differential gene expression analysis.XLSX
Understanding the molecular mechanism of clear cell renal cell carcinoma (ccRCC) is essential for predicting the prognosis and developing new targeted therapies. Our study is to identify hub genes rel
NIAID Data Ecosystem20
Table_1_Identification Hub Genes in Colorectal Cancer by Integrating Weighted Gene Co-Expression Network Analysis and Clinical Validation in vivo and vitro.xlsx
Colorectal cancer (CRC) is the third leading cause of death in the world. However, the key roles of most molecules in CRC remain unclear. This study aimed to identify key modules and hub genes associa
NIAID Data Ecosystem10
Overview of analyses on hub identification.
Overview of all hub identification results on the simulated and biological datasets. Hub AUCs were only calculated for the large networks since they are only of little relevance for small networks. Ea
NIAID Data Ecosystem00
Table S11. WGCNA Hub Genes
Top 10 hub genes per WGCNA module ranked by module membership × intramodular connectivity. Contains 100 genes with FlyBase IDs, gene symbols, module assignment, and hub metrics. CSV format, 101 rows i
NIAID Data Ecosystem10
Additional file 1 of Identifying hub genes of sepsis-associated and hepatic encephalopathies based on bioinformatic analysis—focus on the two common encephalopathies of septic cirrhotic patients in ICU
Additional file 1: Table S1. The genes list of Green and Turquoise modules.
NIAID Data Ecosystem00
