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

Gene expression signature‐based prognostic risk score in patients with glioblastoma

7 Jun 2013

Abstract excerpt

The present study aimed to identify genes associated with patient survival to improve our understanding of the underlying biology of gliomas. We investigated whether the expression of genes selected using random survival forests models could be used to define glioma subgroups more objectively than standard pathology. The RNA from 32 non-treated grade 4 gliomas were analyzed using the GeneChip Human Genome U133...

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 Radiomics and Machine Learning in Medical Imaging

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 23745793
DOI: 10.1111/cas.12214

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 8 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Gene expression signature‐based prognostic risk score in patients with glioblastomaPMID 23745793Read ↗

A RNA sequencing-based six-gene signature for survival prediction in patients with glioblastomaSemantic proximity Read ↗

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

A 5‐gene prognostic nomogram predicting survival probability of glioblastoma patientsSemantic proximity Read ↗

Gene Expression Profiling of Gliomas Strongly Predicts SurvivalSemantic proximity Read ↗

Machine Learning based Survival Group Prediction in Glioblastoma<strong> </strong>Semantic proximity Read ↗

Gene Expression Patterns Associated with Survival in GlioblastomaSemantic proximity Read ↗

Five Genes Associated With Survival in Patients With Lower-grade Gliomas Were Identified by Information-theoretical AnalysisSemantic proximity Read ↗

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

Clinical and molecular models of Glioblastoma multiforme survivalSemantic proximity Read ↗

A 35-gene signature discriminates between rapidly- and slowly-progressing glioblastoma multiforme and predicts survival in known subtypes of the cancerSemantic proximity Read ↗

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

A 6-Gene Risk Signature Predicts Survival of Glioblastoma MultiformeSemantic proximity Read ↗

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