首页/数据集/Development of gene expression signatures for miR-340 overexpressing human glioma-initiating cells (GICs)

Development of gene expression signatures for miR-340 overexpressing human glioma-initiating cells (GICs)

ChEBI2015-04-07 更新2026-07-21 收录

神经胶质瘤分子病理学

基因表达特征分析

数据链接：

https://www.ebi.ac.uk/biostudies/ArrayExpress/studies/E-GEOD-61078 数据链接链接失效反馈

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资源简介：

Development of gene expression signatures for miR-340 overexpressing human glioma-initiating cells (GICs)

应用场景：

创建时间：

2015-04-07

卵巢癌耐药性

基因表达特征分析

The majority of ovarian tumors eventually recur in a drug resistant form. Using cisplatin sensitive and resistant cell lines assembled into 3D spheroids we profiled gene expression and identified cand

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Design of a gene signature to analyze the proinflammatory and the profibrotic polarization of murine fibroblasts and validation in an experimental murine model of scleroderma.. Design of a gene signature to analyze the proinflammatory and the profibrotic polarization of murine fibroblasts and validation in an experimental murine model of scleroderma.

纤维化疾病

基因表达特征分析

Effect of TGFb1, TNFa, IL6-IL6R, IL1b on gene expression in Mouse Embryonnic Fibrobroblasts (3T3) using RNA microarrays. Overall design: Enrichment analysis of the differentially expressed genes (DEGs

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Supplementary Table 4 from ALDH1-Positive Cancer Stem Cells Predict Engraftment of Primary Breast Tumors and Are Governed by a Common Stem Cell Program

乳腺癌干细胞

基因表达特征分析

Table SIII. Breast cancer stem cell gene expression signature (BCSC-GES)

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Expression profiling defines a recurrence signature in lung adenocarcinoma

肺腺癌复发预测

基因表达特征分析

Lung cancer remains the leading cause of cancer death worldwide. Overall 5-year survival is about 10-15% and despite curative intent surgery, treatment failure is primarily due to recurrent disease. C

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Additional file 2: Table S2. of Discovering gene expression signatures responding to tyrosine kinase inhibitor treatment in chronic myeloid leukemia

慢性粒细胞白血病治疗

基因表达特征分析

Lists of functional annotation terms of differentially expressed genes of each dataset (GSE14671, GSE2535, and GSE33224). (XLS 143Â kb)

Figshare2016-12-15 更新50