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Posted: 2025-04-24 11:19:57 UTC
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
This article contains some claims that remain unverified. While much of the content may be accurate, exercise care when relying on this information.
Status
Last Updated
2025-04-24 11:20:25 UTC
Verified By
Rollup News
This study investigates age-related epigenetic changes in the brain using multi-modal epigenetic data, revealing cell-type-specific transposon demethylation, TAD remodeling, and a deep learning framework to predict transcriptional changes.
Cell-type-specific transposon demethylation
Age-related methylation affects non-neuronal populations
Emergence of smaller TADs in excitatory neurons
Deep learning model predicts age-related transcriptional changes
Understanding the complex interplay of epigenetic factors in brain aging
Deciphering the cell-type-specific mechanisms driving neurodegenerative diseases
Developing effective deep learning models to predict age-related transcriptional changes