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Table S3 from Genomic and Expression Analyses Define MUC17 and PCNX1 as Predictors of Chemotherapy Response in Breast Cancer

NIAID Data Ecosystem2026-04-25 收录

放化疗反应预测

体细胞变异生物标志物

数据链接：

https://figshare.com/articles/dataset/Table_S3_from_Genomic_and_Expression_Analyses_Define_MUC17_and_PCNX1_as_Predictors_of_Chemotherapy_Response_in_Breast_Cancer/22519098 数据链接链接失效反馈

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Somatic variants data

应用场景：

创建时间：

2020-03-01

放化疗反应预测

基因表达生物标志物

Genes with a significantly lower expression in patients predicted to not achieve a pCR with an extremely low predicted probability of pCR (a) and enes with a significantly higher expression in patient

NIAID Data Ecosystem60

DataSheet_1_Ferroptosis-Associated Molecular Features to Aid Patient Clinical Prognosis and Therapy Across Human Cancers.xlsx

癌症铁死亡预后

放化疗反应预测

Ferroptosis is a new non-apoptotic form that regulates cell death and is mainly dependent on iron-mediated oxidative damage and subsequent cell membrane damage. Ferroptosis may be a potential therapeu

NIAID Data Ecosystem30

Identifying biomarkers predicting response to chemotherapy in Stage II and Stage III colorectal cancer patients. Identifying biomarkers predicting response to chemotherapy in Stage II and Stage III colorectal cancer patients

放化疗反应预测

转录组生物标志物

Defining molecular features that can predict the response to chemotherapy for stage II-III colorectal cancer (CRC) patients remains challenging in cancer research. Most available clinical samples are

NIAID Data Ecosystem20

DataSheet_5_Multiparametric MRI Radiomics for the Early Prediction of Response to Chemoradiotherapy in Patients With Postoperative Residual Gliomas: An Initial Study.doc

放化疗反应预测

神经胶质瘤

PurposeTo evaluate whether multiparametric magnetic resonance imaging (MRI)-based logistic regression models can facilitate the early prediction of chemoradiotherapy response in patients with residual

NIAID Data Ecosystem50

DruID dataset: A multi-task domain-adapted model to predict chemotherapy response from mutations in recurrently altered cancer genes

放化疗反应预测

癌症基因组数据

This repository contains data used for the paper `A multi-task domain-adapted model to predict chemotherapy response from mutations in recurrently altered cancer genes`. It contains both processed v

NIAID Data Ecosystem20

Table S3 from Genomic and Expression Analyses Define MUC17 and PCNX1 as Predictors of Chemotherapy Response in Breast Cancer

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