ArticleFrontiers in immunology2021
Cross-Tissue Transcriptomic Analysis Leveraging Machine Learning Approaches Identifies New Biomarkers for Rheumatoid Arthritis.
Article in Frontiers in immunology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
22 citing papers in PubMed, 40 citations in OpenAlex.
- Integrative Transcriptomic and Network Analysis of Shared Osteo-Immune Regulatory Programs in Postmenopausal Osteoporosis and Osteosarcoma Within Central Mexican Cohorts.Current issues in molecular biology · 2026Article
- Peripheral blood transcriptomic analysis of patients with rheumatoid arthritis associated interstitial lung disease reveals: distinct molecular signature with evidence of humoral and myeloid immunity.Arthritis research & therapy · 2026Article
- MMP3C v2: a network-based framework decoding metabolic plasticity in rheumatoid arthritis, enabling accurate diagnosis and uncovering cell-type-specific metabolic rewiring.Briefings in bioinformatics · 2026Article
- Small data, big challenges: Machine- and deep-learning strategies for data-limited drug discovery.Advanced drug delivery reviews · 2026Review
- Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis.Medicina (Kaunas, Lithuania) · 2025Article
- Elucidating the Mechanism of VVTT Infection Through Machine Learning and Transcriptome Analysis.International journal of molecular sciences · 2025Article
- BACH1 as a key driver in rheumatoid arthritis fibroblast-like synoviocytes identified through gene network analysis.Life science alliance · 2025Article
- Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis.Therapeutic advances in musculoskeletal disease · 2025Review
- Single-cell RNA-Seq analysis reveals cell subsets and gene signatures associated with rheumatoid arthritis disease activity.JCI insight · 2024Article
- Gene Network Analyses Identify Co-regulated Transcription Factors and BACH1 as a Key Driver in Rheumatoid Arthritis Fibroblast-like Synoviocytes.bioRxiv : the preprint server for biology · 2024Article
- Whole blood transcriptomics reveals the enrichment of neutrophil activation pathways during erythema nodosum leprosum reaction.Frontiers in immunology · 2024Article
- Cell-specific gene networks and drivers in rheumatoid arthritis synovial tissues.Frontiers in immunology · 2024Article
- MaLiAmPi enables generalizable and taxonomy-independent microbiome features from technically diverse 16S-based microbiome studies.Cell reports methods · 2023Article
- Article
- A survey of artificial intelligence in rheumatoid arthritis.Rheumatology and immunology research · 2023Article
- HSP90β promotes osteoclastogenesis by dual-activation of cholesterol synthesis and NF-κB signaling.Cell death and differentiation · 2023Article
- Identification of immunogenic cell death-related signature on prognosis and immunotherapy in kidney renal clear cell carcinoma.Frontiers in immunology · 2023Article
- Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review.Rheumatology and therapy · 2022Review
- Article
- Identification and Validation of Hub Genes for Predicting Treatment Targets and Immune Landscape in Rheumatoid Arthritis.BioMed research international · 2022Article
Corrections and comments
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Authors and funding
12 authors at 3 institutions in 1 country.
Funding
Abstract
There is an urgent need to identify biomarkers for diagnosis and disease activity monitoring in rheumatoid arthritis (RA). We leveraged publicly available microarray gene expression data in the NCBI GEO database for whole blood (N=1,885) and synovial (N=284) tissues from RA patients and healthy controls. We developed a robust machine learning feature selection pipeline with validation on five independent datasets culminating in 13 genes:
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.