Unknown

Dataset Information

Identification of Prognostic Markers of DNA Damage and Oxidative Stress in Diagnosing Papillary Renal Cell Carcinoma Based on High-Throughput Bioinformatics Screening.


ABSTRACT:

Purpose

Papillary renal cell carcinoma (pRCC) is the second most common histological subtype of adult kidney tumors, with a poor prognosis due to limited understanding of the disease mechanism. Herein, we have performed high-throughput bioinformatic screening to explore and identify potential biomarkers of DNA damage and oxidative stress for pRCC.

Methods

RNA sequencing data related to pRCC were downloaded from the TCGA database, and differentially expressed genes (DEG) were identified by a wide variety of clustering and classification algorithms, including self-organized maps (SOM), artificial neural networks (ANN), support vector machines (SVM), fuzzy logic, and hyphenated techniques such as neuro-fuzzy networks. Then DAVID and STRING online biological information tools we

SUBMITTER: Li L 

PROVIDER: S-EPMC9922175 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature