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

Identification of transcription factors associated with the disease-free survival of triple-negative breast cancer through weighted gene co-expression network analysis

23 Dec 2024

Abstract excerpt

Objective: Triple-negative breast cancer (TNBC) is a subtype of breast cancer that has a worse prognosis than the other subtypes of breast cancer because of its high recurrence and metastasis rates. The objective of this study is to identify the regulatory factors that are associated with the disease-free survival (DFS) of TNBC and potential biomarkers for TNBC treatment. Material and Methods: We obtained the...

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 Ferroptosis and cancer prognosis
Share to FOXO transcription factor regulation

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 39917004
DOI: 10.25259/cytojournal_127_2024

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

Identification of transcription factors associated with the disease-free survival of triple-negative breast cancer through weighted gene co-expression network analysisPMID 39917004Read ↗

Identification of novel prognostic genes of triple-negative breast cancer using meta-analysis and weighted gene co-expressed network analysisSemantic proximity Read ↗

Transcriptome-Based Network Analysis Unveils Eight Immune-Related Genes as Molecular Signatures in the Immunomodulatory Subtype of Triple-Negative Breast CancerSemantic proximity Read ↗

Identification of hub genes and diagnostic efficacy for triple-negative breast cancer through WGCNA and Mendelian randomizationSemantic proximity Read ↗

Identification of hub genes affecting triple-negative breast cancer using bioinformatics analysis strategiesSemantic proximity Read ↗

Using Weighted Gene Co-Expression Network Analysis to Identify Increased MND1 Expression as a Predictor of Poor Breast Cancer SurvivalSemantic proximity Read ↗

Identification of potential core genes in triple negative breast cancer using bioinformatics analysisSemantic proximity Read ↗

Identification of potential key genes and pathways predicting pathogenesis and prognosis for triple-negative breast cancerSemantic proximity Read ↗

Weighted Gene Co-expression Network Analysis Identifies TBC1D10C as A New Prognostic Biomarker for Breast CancerSemantic proximity Read ↗

Combination of Immune-Related Network and Molecular Typing Analysis Defines a Three-Gene Signature for Predicting Prognosis of Triple-Negative Breast CancerSemantic proximity Read ↗

Insights into Breast Cancer Prognosis: A Differential Regulatory Network Approach to Identify Key Transcription Factor BiomarkersSemantic proximity Read ↗

An Immune-Related Gene Prognostic Index for Triple-Negative Breast Cancer Integrates Multiple Aspects of Tumor-Immune MicroenvironmentSemantic proximity Read ↗

Identification of a Novel Transcription Factor Prognostic Index for Breast CancerSemantic proximity Read ↗

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