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

Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypes

6 Feb 2014

Abstract excerpt

Molecular stratification of tumors is essential for developing personalized therapies. Although patient stratification strategies have been successful; computational methods to accurately translate the gene-signature from high-throughput platform to a clinically adaptable low-dimensional platform are currently lacking. Here, we describe PIGExClass (platform-independent isoform-level gene-expression based...

Read the complete abstract on PubMed

Topics

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

Share to Bioinformatics and Genomic Networks
Share to Gene expression and cancer classification
Share to Glioma Diagnosis and Treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 24503249
DOI: 10.1093/nar/gku121

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

Isoform-level gene signature improves prognostic stratification and accurately classifies glioblastoma subtypesPMID 24503249Read ↗

Relevance of a TCGA-derived Glioblastoma Subtype Gene-Classifier among Patient PopulationsSemantic proximity Read ↗

Gene Expression Profiling Stratifies IDH-Wildtype Glioblastoma With Distinct PrognosesSemantic proximity Read ↗

A Novel Molecular Classification Method for Glioblastoma Based on Tumor Cell Differentiation TrajectoriesSemantic proximity Read ↗

Identification of five important genes to predict glioblastoma subtypesSemantic proximity Read ↗

Comparative analysis of transcriptomic profile, histology, and IDH mutation for classification of gliomas.Semantic proximity Read ↗

Unveiling divergent treatment prognoses in IDHwt-GBM subtypes through multiomics clustering: a swift dual MRI-mRNA model for precise subtype prediction.Semantic proximity Read ↗

Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosisSemantic proximity Read ↗

A Deep Learning–Based Framework for Supporting Clinical Diagnosis of Glioblastoma SubtypesSemantic proximity Read ↗

Reboot: a straightforward approach to identify genes and splicing isoforms associated with cancer patient prognosisSemantic proximity Read ↗

Solid Tumors Pan Cancer Transcriptome: Tissue/Cancer specific expression groups at the Isoform-LevelSemantic proximity Read ↗

Dynamic Quantum Clustering of Gliomas RNA-seq Identifies Diagnostic Separation and Survival GradientsSemantic proximity Read ↗

Clinical and Molecular Recursive Partitioning Analysis of High-grade Glioma Treated With IMRT.Semantic proximity Read ↗

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