Resectable gastric cancer prognosis study by multiple omics. undefined

NIAID Data Ecosystem2026-05-01 收录

癌症预后预测

生物标志物研究

数据链接：

https://www.ncbi.nlm.nih.gov/bioproject/PRJEB61171 数据链接链接失效反馈

官方服务：

资源简介：

Resectable gastric cancer prognosis study by multiple omics

创建时间：

2023-04-05

mRNA Seq.zip

生物标志物研究

慢性萎缩性胃炎

The aim of the study is to explore biomarkers of intestinal metaplasia associated with chronic atrophic gastritis. Here is the raw data of DEGs via transcriptomics sequencing.

NIAID Data Ecosystem20

Cox regression analysis to identify predictors of EC development.

癌症预后预测

生存分析

Cox regression analysis to identify predictors of EC development.

NIAID Data Ecosystem20

Table_1_A novel risk score model based on gamma-aminobutyric acid signature predicts the survival prognosis of patients with breast cancer.xlsx

癌症预后预测

肿瘤免疫微环境分析

BackgroundGamma-aminobutyric acid (GABA) participates in the migration, differentiation, and proliferation of tumor cells. However, the GABA-related risk signature has never been investigated. Hence,

NIAID Data Ecosystem10

Table_1_Tumor-Infiltrating Lymphocyte-Based Risk Score for Predicting Prognosis in Gastric Cancer.XLSX

癌症预后预测

肿瘤免疫微环境

Tumor-infiltrating lymphocytes (TILs) in gastric cancer are closely related to clinical prognosis; however, little is known regarding the immune microenvironment in this disease. Thus, RNA-sequencing

NIAID Data Ecosystem20

DataSheet_1_A novel risk score model based on gamma-aminobutyric acid signature predicts the survival prognosis of patients with breast cancer.zip

癌症预后预测

肿瘤生物标志物

BackgroundGamma-aminobutyric acid (GABA) participates in the migration, differentiation, and proliferation of tumor cells. However, the GABA-related risk signature has never been investigated. Hence,

NIAID Data Ecosystem10

Resectable gastric cancer prognosis study by multiple omics. undefined

资源简介：

相关数据集