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

A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysis

23 Jul 2023

Abstract excerpt

BACKGROUND: Gastric cancer (GC) ranks among the most common malignancies worldwide. This study aimed to find critical genes/pathways in GC pathogenesis. METHODS: Gene interactions were analyzed, and the protein-protein interaction network was drawn. Then enrichment analysis of the hub genes was performed and network cluster analysis and promoter analysis of the hub genes were done. Age/sex analysis was done on...

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 GDF15 and Related Biomarkers

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 37482618
DOI: 10.1186/s12876-023-02891-4

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

A systems biology approach to pathogenesis of gastric cancer: gene network modeling and pathway analysisPMID 37482618Read ↗

A Systems Biology Approach to Pathogenesis of Gastric Cancer: Gene Network Modeling and Pathway AnalysisSemantic proximity Read ↗

Identification of differentially expressed genes associated with the pathogenesis of gastric cancer by bioinformatics analysisSemantic proximity Read ↗

Investigation of the underlying hub genes and molecular pathogenesis in gastric cancer by integrated bioinformatic analysesSemantic proximity Read ↗

Identification of Potential Key Genes Associated With the Pathogenesis and Prognosis of Gastric Cancer Based on Integrated Bioinformatics AnalysisSemantic proximity Read ↗

Identification of Potential Diagnostic and Prognostic Biomarkers for Gastric Cancer Based on Bioinformatic AnalysisSemantic proximity Read ↗

Identification of Key Genes as Potential Drug Targets for Gastric CancerSemantic proximity Read ↗

Bioinformatics and pathway enrichment analysis identified hub genes and potential biomarker for gastric cancer prognosisSemantic proximity Read ↗

Identification of Potential Biomarkers and Therapy Targets involved in Gastric Cancer Using Bioinformatics AnalysisSemantic proximity Read ↗

Integrative bioinformatic characterization of driver genes and prognostic features in human gastric carcinomaSemantic proximity Read ↗

Molecular dysexpression in gastric cancer revealed by integrated analysis of transcriptome dataSemantic proximity Read ↗

Identification of potential key genes in gastric cancer using bioinformatics analysisSemantic proximity Read ↗

Identification of key genes associated with gastric cancer based on DNA microarray dataSemantic proximity Read ↗

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