Discover Community Create You

Loading publication...

Noodle always counts identifier-free feature events for service operation. With your permission, Google Analytics can also estimate audience and engagement. Search text, publication identifiers, cookies, IP addresses and browser fingerprints are never included in Noodle's first-party event counters.

Privacy details

Article

A Novel Prognostic Signature of Transcription Factors for the Prediction in Patients With GBM

1 Oct 2019

Abstract excerpt

Background: Although the diagnosis and treatment of glioblastoma (GBM) is significantly improved with recent progresses, there are still large heterogeneity in therapeutic effects and overall survival. The aim of this study is to analyze gene expressions of transcription factors (TFs) in GBM so as to discover new tumor markers. Methods: Differentially expressed transcription factors are identified by data mining...

Read the complete abstract on PubMed

Topics

Share this publication in a Topic to start or enrich a Post.

Share to Ferroptosis and cancer prognosis
Share to Glioma Diagnosis and Treatment
Share to MicroRNA in disease regulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 31632439
DOI: 10.3389/fgene.2019.00906

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 7 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

A Novel Prognostic Signature of Transcription Factors for the Prediction in Patients With GBMPMID 31632439Read ↗

Identification of Potential Key Genes Associated with the Pathogenesis and Prognosis of Glioblastoma Based on Integrated Bioinformatics AnalysisSemantic proximity Read ↗

Identification of Key Differentially Expressed Transcription Factors in GlioblastomaSemantic proximity Read ↗

Expression Profile Analysis Identifies a Novel Five-Gene Signature to Improve Prognosis Prediction of GlioblastomaSemantic proximity Read ↗

Identification of An Epithelial-Mesenchymal Transition-Related lncRNA Prognostic Signature For Patients With GlioblastomaSemantic proximity Read ↗

Genomic Analysis of Glioblastoma Multiforme Reveals a Key Transcription Factor Signature Relevant to Prognosis and the Immune ProcessesSemantic proximity Read ↗

Integrated Analysis to Evaluate the Prognostic Value of Signature mRNAs in Glioblastoma MultiformeSemantic proximity Read ↗

Mining TCGA Database to Construct a RNA Binding Proteins-Related Prognostic Model for GBMSemantic proximity Read ↗

A Novel 16-Genes Signature Scoring System as Prognostic Model to Evaluate Survival Risk in Patients with GlioblastomaSemantic proximity Read ↗

Identification of novel genes associated with diagnosis and prognosis in glioblastomaSemantic proximity Read ↗

Identification of a Novel Eight-Gene Risk Model for Predicting Survival in Glioblastoma: A Comprehensive Bioinformatic AnalysisSemantic proximity Read ↗

A Risk Classification System With Five-Gene for Survival Prediction of Glioblastoma PatientsSemantic proximity Read ↗

Potential therapeutic targets for glioblastoma patients based on a prognostic risk modelSemantic proximity Read ↗

⌁Select a neighboring publication to make it the new centre.