A novel microRNA signature for pathological grading in�lung adenocarcinoma based on TCGA and GEO data-Reference-Cited by-同舟云学术

A novel microRNA signature for pathological grading in�lung adenocarcinoma based on TCGA and GEO data

Published:2020-03-04 Issue: Volume: Page:
ISSN:1107-3756
Container-title:International Journal of Molecular Medicine
language:
Short-container-title:Int J Mol Med

Author:

Yang Zhiyu¹,Yin Hongkun²,Shi Lei³,Qian Xiaohua¹

Affiliation:

1. SJTU‑Yitu Joint Laboratory of Artificial Intelligence in Healthcare, School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai 200030, P.R. China

2. Shanghai Yitu Healthcare Technology Co. Ltd., Shanghai�200051, P.R. China

3. Hangzhou Yitu Healthcare Technology Co. Ltd., Hangzhou, Zhejiang 310012, P.R. China

Publisher

Spandidos Publications

Subject

Genetics,General Medicine

Cited by 12 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Machine learning combining multi-omics data and network algorithms identifies adrenocortical carcinoma prognostic biomarkers;Frontiers in Molecular Biosciences;2023-11-06

2. MOCSS: Multi-omics data clustering and cancer subtyping via shared and specific representation learning;iScience;2023-08

3. Exploration of the Relevance of MicroRNA Signatures for Cancer Detection and Multiclass Cancer Classification;IEEE Access;2023

4. ESOMIR: a curated database of biomarker genes and miRNAs associated with esophageal cancer;Database;2023-01-01

5. TRIM36 enhances lung adenocarcinoma radiosensitivity and inhibits tumorigenesis through promoting RAD51 ubiquitination and antagonizing hsa-miR-376a-5p;Biochemical and Biophysical Research Communications;2022-11