PREDICT

NIAID Data Ecosystem2026-03-10 收录

放化疗反应预测

多药耐药性基因组分析

数据链接：

https://www.omicsdi.org/dataset/ega/EGAS00001000094 数据链接链接失效反馈

官方服务：

资源简介：

PREDICT/Predicting individual response and resistance to VEGFR/mTOR pathway therapeutic intervention using biomarkers discovered through tumour functional genomics.EGA study EGAS00001000094

创建时间：

2017-07-26

Table_4_Identification of Autophagy Related circRNA-miRNA-mRNA-Subtypes Network With Radiotherapy Responses and Tumor Immune Microenvironment in Non-small Cell Lung Cancer.xls

放化疗反应预测

肿瘤免疫微环境分析

Lung cancer (LC) is one of the most frequently diagnosed cancers and the leading cause of cancer death worldwide, and most LCs are non-small cell lung cancer (NSCLC). Radiotherapy is one of the most e

NIAID Data Ecosystem40

DataSheet_1_A novel necroptosis-related lncRNA signature for predicting prognosis and anti-cancer treatment response in endometrial cancer.pdf

子宫内膜癌预后预测

放化疗反应预测

BackgroundNecroptosis, a form of programmed cell death, underlies tumorigenesis and the progression of cancers. Anti-cancer strategies targeting necroptosis have increasingly been shown to present a p

NIAID Data Ecosystem20

Klebsiella pneumoniae strain:109 Genome sequencing and assembly

多药耐药性基因组分析

毒力基因

The bacterium belongs to Klebsiella pneumoniae, and has multi-drug resistance and a high-toxic phenotype at the same time. Sequencing is performed to further study the specific virulence and drug-resi

NIAID Data Ecosystem10

Prediction of sensitivity of rectal cancer cells in response to preoperative chemoradiotherapy by DNA microarray analysis of gene expression profiles.

放化疗反应预测

基因表达生物标志物

Samples were prospectively collected during colonoscopic examination from 46 rectal cancer patients before starting preoperative chemoradiotherapy. The expression profiles were determined using Affyme

NIAID Data Ecosystem40

A six-gene prediction model for tumor response to induction chemotherapy in locoregionally advanced laryngo-hypopharyngeal carcinoma

放化疗反应预测

个体化策略

This study aimed to develop a novel gene expression signature that can predict tumor response to induction chemotherapy (IC) before treatment. RNA sequencing (RNA-seq) was used to screen the different

NIAID Data Ecosystem10

PREDICT

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