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

Multi-omics integration and machine learning define an iron-sulfur cluster/zinc-binding protein prognostic signature in esophageal squamous cell carcinoma

24 Aug 2026

Abstract excerpt

No abstract is available from the source.

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 Esophageal Cancer Research and Treatment
Share to Ferroptosis and cancer prognosis

Source

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Identifiers

PMID: 42637882
DOI: 10.1007/s00335-026-10270-z

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

Multi-omics integration and machine learning define an iron-sulfur cluster/zinc-binding protein prognostic signature in esophageal squamous cell carcinomaPMID 42637882Read ↗

A Stratification System of Ferroptosis and Iron-Metabolism Related Lncrnas Guides the Prediction of The Survival of Patients with Esophageal Squamous Cell CarcinomaSemantic proximity Read ↗

Machine-learning developed an iron, copper, and sulfur-metabolism associated signature predicts lung adenocarcinoma prognosis and therapy responseSemantic proximity Read ↗

Integrated multi-omics profiling yields a clinically relevant molecular classification for esophageal squamous cell carcinomaSemantic proximity Read ↗

Pan‐cancer analysis of iron metabolic landscape across the Cancer Genome AtlasSemantic proximity Read ↗

Exploring CISD1 as a multifaceted biomarker in cancer: Implications for diagnosis, prognosis, and immunotherapeutic responseSemantic proximity Read ↗

Integrated Multi-Omics Analysis Model to Identify Biomarkers Associated With Prognosis of Breast CancerSemantic proximity Read ↗

Integrating Bulk and Single-Cell Transcriptomics with Machine Learning Reveals a Heme Metabolism-Based Panel for Lung Adenocarcinoma Chemotherapy ResistanceSemantic proximity Read ↗

Prognostic Value of Iron Metabolism-Related Genes in Bladder Urothelial CarcinomaSemantic proximity Read ↗

Overview of major molecular alterations during progression from Barrett's esophagus to esophageal adenocarcinomaSemantic proximity Read ↗

STEAP Family Members and Gastric Cancer: Expression Profile and Prognostic ValuesSemantic proximity Read ↗

Multi‐omics analysis reveals that ferroptosis‐related gene CISD2 is a prognostic biomarker of head and neck squamous cell carcinomaSemantic proximity Read ↗

A novel four-gene of iron metabolism-related and methylated for prognosis prediction of hepatocellular carcinomaSemantic proximity Read ↗

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