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Transcriptomic datasets from the Gene Expression Omnibus (GEO) were analyzed to identify 14 differentially expressed m6A RNA methylation regulators in spinal cord injury. The research, authored by Xiaoqin Liu and last updated in May 2026, used machine learning to identify hub genes FTO and YTHDC1 and validated them in an independent dataset and a rat model. The analysis includes immune cell infiltration profiles and single-cell RNA sequencing data.
The dataset is a small supplementary document (74.4 KB); users seeking the raw transcriptomic data may need to access the original GEO studies referenced within.