PLOS
open access
CC BY 4.0
Identification of transcriptomic signatures associated with an ac4C related gene set and candidate expression based clusters in osteoarthritis through integrative bioinformatics
Objective: To identify osteoarthritis (OA) associated transcripts overlapping a predefined N4-acetylcytidine (ac4C) related gene set and evaluate their potential as an exploratory classification signature and basis for expression based clustering. Methods: Five GEO datasets were analyzed using diffe
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Identification of potential biomarkers and therapeutic targets for osteoarthritis associated with arginine and proline metabolism based on transcriptome sequencing and bioinformatics.#378419
- Identification of acetylation-related molecular signatures in knee osteoarthritis patients with significant response to warm-needle acupuncture using machine-learning approaches.#145998
- Identification of Immune-Related Lactylation Genes in Rheumatoid Arthritis With Atherosclerosis: A Comprehensive Analysis Using Bulk and Single-Cell RNA Sequencing Data.#174510
- An epithelial–mesenchymal transition-like synovial stromal-remodeling programme associated with knee osteoarthritis pain: Exploratory transcriptomic discovery and spatial analysis#1148180
- Identification of candidate sex hormone-associated genes and immune infiltration characteristics in osteoarthritis based on bioinformatics analysis and machine learning#275943
Record · ID 1081372
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive