Cargando…
Predicting N6-Methyladenosine Sites in Multiple Tissues of Mammals through Ensemble Deep Learning
N6-methyladenosine (m(6)A) 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 m(6)A transcriptome-wide at base resolution via...
Autores principales: | Luo, Zhengtao, Lou, Liliang, Qiu, Wangren, Xu, Zhaochun, Xiao, Xuan |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9778682/ https://www.ncbi.nlm.nih.gov/pubmed/36555143 http://dx.doi.org/10.3390/ijms232415490 |
Ejemplares similares
-
DLm6Am: A Deep-Learning-Based Tool for Identifying N6,2′-O-Dimethyladenosine Sites in RNA Sequences
por: Luo, Zhengtao, et al.
Publicado: (2022) -
Computational identification of N6-methyladenosine sites in multiple tissues of mammals
por: Dao, Fu-Ying, et al.
Publicado: (2020) -
pSuc-FFSEA: Predicting Lysine Succinylation Sites in Proteins Based on Feature Fusion and Stacking Ensemble Algorithm
por: Jia, Jianhua, et al.
Publicado: (2022) -
Detecting N(6)-methyladenosine sites from RNA transcriptomes using ensemble Support Vector Machines
por: Chen, Wei, et al.
Publicado: (2017) -
pSuc-EDBAM: Predicting lysine succinylation sites in proteins based on ensemble dense blocks and an attention module
por: Jia, Jianhua, et al.
Publicado: (2022)