Decoding the m⁶A epitranscriptomic landscape for biotechnological applications using a direct RNA sequencing approach.

ABSTRACT: Epitranscriptomic modifications, particularly N6-methyladenosine (m⁶A), are crucial regulators of gene expression, influencing processes such as RNA stability, splicing, and translation. Traditional computational methods for detecting m⁶A from Nanopore direct RNA sequencing (DRS) data are constrained by their reliance on experimentally validated labels, often resulting in the underestimation of modification sites. Here, we introduce pum6a, an innovative attention-based framework that integrates positive and unlabeled multi-instance learning (MIL) to address the challenges of incomplete labeling and missing read-level annotations. By combining electrical signal features with base alignment data and employing a weighted Noisy-OR probability mechanism, pum6a achieves enh

SUBMITTER: Liu C 

PROVIDER: S-EPMC11742432 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature