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

Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLE

17 May 2021

Abstract excerpt

We identified abnormally methylated, differentially expressed genes (DEGs) and pathogenic mechanisms in different immune cells of RA and SLE by comprehensive bioinformatics analysis. Six microarray data sets of each immune cell (CD19+ B cells, CD4+ T cells and CD14+ monocytes) were integrated to screen DEGs and differentially methylated genes by using R package “limma.” Gene ontology annotations and KEGG analysis...

Read the complete abstract on PubMed

Topics

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

Share to Acute Myeloid Leukemia Research
Share to Immune cells in cancer
Share to Myeloproliferative Neoplasms: Diagnosis and Treatment

Methodology Data sources Editorial policy Privacy About Contact Helena Bioinformatics

Source

Identifiers

PMID: 34079550
DOI: 10.3389/fimmu.2021.668007

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

Comparative Analysis on Abnormal Methylome of Differentially Expressed Genes and Disease Pathways in the Immune Cells of RA and SLEPMID 34079550Read ↗

Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysisSemantic proximity Read ↗

Three hematologic/immune system-specific expressed genes are considered as the potential biomarkers for the diagnosis of early rheumatoid arthritis through bioinformatics analysisSemantic proximity Read ↗

Analysis and identification of the common genes and molecular pathways of Systemic lupus erythematosus and Rheumatoid arthritisSemantic proximity Read ↗

Identification of key biomarkers and immune infiltration in Minimal Change Disease: Novel Insights from bioinformatics analysisSemantic proximity Read ↗

Identification of differentially expressed immune-related genes in patients with systemic lupus erythematosus and the development of a hub gene-based diagnostic modelSemantic proximity Read ↗

Identification of key genes and immune profile in rheumatoid arthritis by bioinformatics analysisSemantic proximity Read ↗

Identification of Potential Biomarkers in PBMC of Systemic Lupus Erythematosus: Results from Bioinformatic AnalysisSemantic proximity Read ↗

Identification of key biomarkers and immune infiltration in systemic lupus erythematosus by integrated bioinformatics analysisSemantic proximity Read ↗

Bioinformatics Analysis Screened and Identified Key Genes, miRNAs and TFs as Potential Biomarkers for Progression of Rheumatoid ArthritisSemantic proximity Read ↗

Identification of Potential Biomarkers in Synovial Tissue of Rheumatoid Arthritis via Integrated Microarray Analysis. Identification of Biomarkers of Rheumatoid ArthritisSemantic proximity Read ↗

Exploring the shared molecular mechanisms between systemic lupus erythematosus and primary Sjögren’s syndrome based on integrated bioinformatics and single-cell RNA-seq analysisSemantic proximity Read ↗

Comprehensive Analysis of Epigenetic Modifications and Immune-Cell Infiltration In Tissues from Patients With Systemic Lupus ErythematosusSemantic proximity Read ↗

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