Predicting N6-Methyladenosine Sites in Multiple Tissues of Mammals through Ensemble Deep Learning.

ABSTRACT: N6-methyladenosine (m⁶A) is the most abundant within eukaryotic messenger RNA modification, which plays an essential regulatory role in the control of cellular functions and gene expression. However, it remains an outstanding challenge to detect mRNA m⁶A transcriptome-wide at base resolution via experimental approaches, which are generally time-consuming and expensive. Developing computational methods is a good strategy for accurate in silico detection of m⁶A modification sites from the large amount of RNA sequence data. Unfortunately, the existing computational models are usually only for m⁶A site prediction in a single species, without considering the tissue level of species, while most of them are constructed based on low-confidence level data

SUBMITTER: Luo Z 

PROVIDER: S-EPMC9778682 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature