Back to search

Article

Identification of hub genes and potential molecular mechanisms in medulloblastoma by integrated bioinformatics analysis

2022-09-22

Abstract excerpt

<h4>Background: </h4> Medulloblastoma (MB) is the most prevalent malignant brain cancer in children. Alterations in genes are critical in the molecular pathogenesis of medulloblastoma. Herein, we propose to explore the potential biomarkers for medulloblastoma and further elucidate their possible molecular mechanism. Methods: Medulloblastoma data sets were abstracted from the GEO (Gene Expression Omnibus) data reso...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work
1e0b2ed1-ba4d-5995-8c01-6f831f0782c8
DOI
10.21203/rs.3.rs-2067914/v1
Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest
Interactive article relationship graphSelect a related publication card to move it into the centre and load its closest explainable connections. Solid lines are source-backed structured connections. Dashed lines are semantic discovery signals and are not scientific evidence.
Identification of hub genes and potential molecular mechanisms in medulloblastoma by integrated bioinformatics analysisDOI 10.21203/rs.3.rs-2067914/v1
Bioinformatics Analysis of Key Genes and Pathways for Medulloblastoma as a Therapeutic TargetSemantic proximity
Integrated Analysis of Transcriptome Data Revealed AURKA and KIF20A as Critical Genes in Medulloblastoma ProgressionSemantic proximity
Gene Expression Analysis Reveals Novel Gene Prognostic Signatures Involved in Medulloblastoma SubgroupsSemantic proximity
Identification of a Twelve-Gene Signature and Establishment of a Prognostic Nomogram Predicting Overall Survival for MedulloblastomaSemantic proximity
Comprehensive analysis reveals independent prognostic biomarkers in glioblastomaSemantic proximity
In-Depth Summary of Intersected Hub-Genes Between Low-Grade and High-Grade Gliomas, from Bioinformatics and Literature ReportsSemantic proximity
Identification of potential crucial genes and molecular mechanisms in glioblastoma multiforme by bioinformatics analysisSemantic proximity
Identification of key candidate genes and pathways in glioblastoma by integrated bioinformatical analysisSemantic proximity
Identification of potential core genes as potential biomarkers for predicting progress and prognosis in glioblastomaSemantic proximity
In silico analysis for potential proteins and microRNAs in Glioblastoma and ParkinsonismSemantic proximity
Construct ion of co - expression modules related to survival by WGCNA and identif ication of potential prognostic biomarkers in glioblastomaSemantic proximity
Integrative bioinformatics analysis for identification of hub genes and pathways responsible for early pathogenesis of retinoblastomaSemantic proximity
Select a neighboring publication to make it the new centre.