Table 3 - The shared biomarkers and immune landscape in psoriatic arthritis and rheumatoid arthritis: Findings based on bioinformatics, machine learning and single-cell analysis

Table 3 - The shared biomarkers and immune landscape in psoriatic arthritis and rheumatoid arthritis: Findings based on bioinformatics, machine learning and single-cell analysis

Table 3 - <p>The shared biomarkers and immune landscape in psoriatic arthritis and rheumatoid arthritis: Findings based on bioinformatics, machine learning and single-cell analysis</p>

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Bibliographic Details
Main Author:	Kaiyi Zhou (2553352) (author)
Other Authors:	Siyu Luo (11856014) (author), Qinxiao Wang (20141557) (author), Sheng Fang (709608) (author)
Published:	2024
Subjects:	Biophysics Cell Biology Genetics Molecular Biology Immunology Developmental Biology Cancer Hematology Biological Sciences not elsewhere classified receiver operating characteristic nf -&# 954 lymphocyte antigen 96 least absolute shrinkage inflammatory musculoskeletal disorders constructed using data b signaling pathways gsea analysis indicated gene expression omnibus gap junction function cell sequencing data enhanced vegf signaling seven overlapping degs decision curve analysis immune cell function two marker genes tf network suggested potential diagnostic markers study identified rpl22l1 vegf signaling results indicated potential association marker genes high expression gap junctions diagnostic capacity cell infiltration cell development cell communication immune landscape immune infiltrates immune cells xlink "> utilized datasets transcription factor thereby exploring shared biomarkers selection operator rheumatoid arthritis rfe ). psoriatic arthritis nk cells mechanistic similarities machine learning like receptors like 1 key biomarkers investigations demonstrated findings based experimental approaches dca ). comprehensive understanding common types cellular subpopulations cells examined
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