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 potential target genes of non-small cell lung cancer in response to resveratrol treatment by bioinformatics analysis

11 Oct 2021

Abstract excerpt

Non-small cell lung cancer (NSCLC) is the most common type in lung cancer in the world, and it severely threatens the life of patients. Resveratrol has been reported to inhibit cancer. However, mechanisms of resveratrol inhibiting NSCLC were unclear. The aim of this study was to identify differentially expressed genes (DEGs) of NSCLC treated with resveratrol and reveal the potential targets of resveratrol in...

Read the complete abstract on PubMed

Topics

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

Share to RNA modifications and cancer
Share to Sirtuins and Resveratrol in Medicine
Share to Tannin, Tannase and Anticancer Activities

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 34633989
DOI: 10.18632/aging.203616

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

Identification of potential target genes of non-small cell lung cancer in response to resveratrol treatment by bioinformatics analysisPMID 34633989Read ↗

Identification of differentially expressed genes in non-small cell lung cancerSemantic proximity Read ↗

Identification of Biomarker Signatures and Candidate Drugs in Non-Small Cell Lung CancerSemantic proximity Read ↗

Identification of key genes in non-small cell lung cancer by bioinformatics analysisSemantic proximity Read ↗

Identification and validation of key genes associated with non‐small‐cell lung cancerSemantic proximity Read ↗

Prognostic significance of TOP2A in non-small cell lung cancer revealed by bioinformatic analysisSemantic proximity Read ↗

Identification of key differentially expressed genes associated with non‑small cell lung cancer by bioinformatics analysesSemantic proximity Read ↗

Bioinformatics analysis of differentially expressed genes in tumor and paracancerous tissues of patients with lung adenocarcinomaSemantic proximity Read ↗

Identidication of novel biomarkers in non-small cell lung cancer using machine learningSemantic proximity Read ↗

Identifying differentially expressed genes and pathways in two types of non-small cell lung cancer: adenocarcinoma and squamous cell carcinomaSemantic proximity Read ↗

Identification of Key Genes and Pathways in Female Lung Cancer Patients Who Never Smoked by a Bioinformatics AnalysisSemantic proximity Read ↗

Prognostic significance and molecular mechanisms of LPCAT1 in lung squamous cell carcinomaSemantic proximity Read ↗

Identification of biomarkers, pathways and potential therapeutic targets for EGFR-TKI resistance in non-small-cell lung cancerSemantic proximity Read ↗

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