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

Establishment of a novel glycolysis-immune-related diagnosis gene signature for endometriosis by machine learning

17 Mar 2023

Abstract excerpt

PURPOSE: The objective of this study was to investigate the key glycolysis-related genes linked to immune cell infiltration in endometriosis and to develop a new endometriosis (EMS) predictive model. METHODS: A training set and a test set were created from the Gene Expression Omnibus (GEO) public database. We identified five glycolysis-related genes using least absolute shrinkage and selection operator (LASSO)...

Read the complete abstract on PubMed

Topics

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

Share to Connective Tissue Growth Factor Research
Share to Endometriosis Research and Treatment
Share to Reproductive System and Pregnancy

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 36930359
DOI: 10.1007/s10815-023-02769-0

Provenance

PubMed metadata and Literature Corpus relationships. Corpus snapshot updated 2 Sept 2026.

Related research

Semantic proximity does not establish scientific evidence.

Research trail→

Click a neighbor to travelStep 1 · 12 closest

Establishment of a novel glycolysis-immune-related diagnosis gene signature for endometriosis by machine learningPMID 36930359Read ↗

Establishment Of A Novel Glycolysis-Immune-Related Diagnosis Gene Signature For Endometriosis By Machine LearningSemantic proximity Read ↗

Comprehensive Analysis of the Glycolysis-Related Gene Prognostic Signature and Immune Infiltration in Endometrial CancerSemantic proximity Read ↗

Comprehensive Analysis of the Association Between the Glycolysis Prognostic Risk Signature and Immune Infiltration in Endometrial CancerSemantic proximity Read ↗

Identification and Diagnostic Potential of Pyroptosis-Related Genes in Endometriosis: A Novel Bioinformatics AnalysisSemantic proximity Read ↗

Integrated bioinformatics analysis uncovers characteristic genes and molecular subtyping system for endometriosisSemantic proximity Read ↗

Identification and validation of a novel glycolysis-related gene signature for predicting the prognosis in ovarian cancerSemantic proximity Read ↗

Identification of molecular subtypes and immune infiltration in endometriosis: a novel bioinformatics analysis and In vitro validationSemantic proximity Read ↗

Identification and Exploration of Novel Macrophage M2-Related Biomarkers and Potential Therapeutic Agents in EndometriosisSemantic proximity Read ↗

Identification of Key Glycolysis-Related Genes in Osteoarthritis and Their Correlation with Immune Infiltration Using Bioinformatics Analysis and Machine LearningSemantic proximity Read ↗

Bioinformatics identification and validation of biomarkers and infiltrating immune cells in endometriosisSemantic proximity Read ↗

Identification of key immune genes of endometriosis based on bioinformatics and machine learningSemantic proximity Read ↗

Machine Learning Algorithms for a Novel Cuproptosis-related Gene Signature of Diagnostic and Immune Infiltration in EndometriosisSemantic proximity Read ↗

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