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Article

Whole-Genome Expression Microarray Combined with Machine Learning to Identify Prognostic Biomarkers for High-Grade Glioma.

Journal of molecular neuroscience : MN - 1 Apr 2018

Shu Chang, Wang Qiong, Yan Xiaoling, Wang Jinhuan

Abstract excerpt

The aim of our study is to build a framework for a better understanding of high-grade glioma (HGG) prognostic-related biomarkers. Whole-genome gene expression microarray was performed to identify differently expressed genes between HGGs and low-grade diffuse gliomas. Several machine learning algorithms were used to filter prognostic-related genes. One hundred ninety-three HGG patients after surgical resection...

Topics

Biomarkers, Tumor
Brain Neoplasms
Cell Cycle Proteins
Cell Line, Tumor
Cell Movement
DNA Modification Methylases
DNA Repair Enzymes
Female
Gene Expression Profiling
Glioma
Humans

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Insulin-Like Growth Factor II

Machine Learning

Male

Membrane Glycoproteins

Mutation

Nuclear Proteins

Protein-Tyrosine Kinases

Source

Identifiers

PMID: 29502292
DOI: 10.1007/s12031-018-1049-7

Genes

WEE1
EMP3
IDH1
MGMT

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 31 Aug 2026.

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