Computational advances in epigenetic regulation databases and prediction tools.

Integrated resources and multi-algorithm prediction tools for epigenetic regulation are expanding across DNA methylation, histone modification, RNA modification, ncRNAs, and disease-linked marks, with AI improving site prediction and functional mining.

• Why it matters: Epigenetic dysregulation is linked to many diseases, but existing overviews often cover only one modification type, leaving a gap in systematic guidance across integrated databases and prediction approaches.
• What they did: The work surveys major databases and prediction tools spanning DNA methylation, histone modification, RNA modification, ncRNAs, and disease-related epigenetic modifications, emphasizing machine learning and deep learning for faster, more accurate computational analyses.
• The result: The review consolidates current capabilities and highlights challenges and future directions, aiming to help researchers select data repositories and tools for epigenetic mechanism and pharmaceutical research.

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