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Additional file 1 of Identifying network biomarkers of cancer by sample-specific differential network

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https://figshare.com/articles/dataset/Additional_file_1_of_Identifying_network_biomarkers_of_cancer_by_sample-specific_differential_network/20076681 数据链接链接失效反馈

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Additional file 1. The cancer gene of BRCA.

应用场景：

创建时间：

2022-06-15

癌症生物标志物

肿瘤分子靶向治疗

5-Methylcytosine (m5C) is a kind of methylation modification that occurs in both DNA and RNA and is present in the highly abundant tRNA and rRNA. It has an important impact on various human diseases i

NIAID Data Ecosystem20

Table_2_Bioinformatics-Driven Identification of p62 as A Crucial Oncogene in Liver Cancer.xlsx

癌症生物标志物

癌症分子机制

Liver hepatocellular carcinoma (LIHC) is the major form of liver cancer that is the fourth most common cause of cancer death worldwide. It has been reported that the multifunctional protein p62 (also

NIAID Data Ecosystem10

Data Sheet 7_Effect of immune infiltration intensity on the efficacy of neoadjuvant immunotherapy for esophageal cancer.pdf

肿瘤治疗响应

癌症生物标志物

BackgroundEsophageal squamous cell carcinoma (ESCC) treatment often involves neoadjuvant therapy combining chemotherapy and immune checkpoint inhibitors. However, the effectiveness of these treatments

NIAID Data Ecosystem00

Table4_Screening and Comprehensive Analysis of Cancer-Associated tRNA-Derived Fragments.XLSX

癌症生物标志物

非编码RNA功能分析

tRNA-derived fragments (tRFs) constitute a novel class of small non-coding RNA cleaved from tRNAs. In recent years, researches have shown the regulatory roles of a few tRFs in cancers, illuminating a

NIAID Data Ecosystem10

Table_4_The Expression and Effection of MicroRNA-499a in High-Tobacco Exposed Head and Neck Squamous Cell Carcinoma: A Bioinformatic Analysis.XLSX

癌症生物标志物

肿瘤分子流行病学

Background: Few studies have directly investigated the differential expression of microRNAs (miRNAs) in head and neck squamous cell carcinoma (HNSCC) with low, medium, and high tobacco exposure. The p

NIAID Data Ecosystem10

Additional file 1 of Identifying network biomarkers of cancer by sample-specific differential network

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