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Predictive Epitranscriptomics: Computational Identification of m6A Methylation Patterns Associated with Future β-Cell Dysfunction and Hyperglycemic Transition

2025-12-09

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<title>Abstract</title> <p>Objective To develop a computational framework integrating m6A methylation profiles with machine learning to identify patterns predictive of future β-cell dysfunction and hyperglycemic transition. Methods We performed a multi-phase bioinformatics analysis of transcriptome-wide m6A and RNA-seq data from human pancreatic islets across normoglycemic, prediabetic, and T2DM states. Different...

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Literature Corpus work
f3abd7b0-3d04-5f9d-abc7-769ebcdf34df
DOI
10.21203/rs.3.rs-8302280/v1
Open publication

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Predictive Epitranscriptomics: Computational Identification of m6A Methylation Patterns Associated with Future β-Cell Dysfunction and Hyperglycemic TransitionDOI 10.21203/rs.3.rs-8302280/v1
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