DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N(6)-methyladenosine on RNA

Models developed using Nanopore direct RNA sequencing data from in vitro synthetic RNA with all adenosine replaced by N(6)-methyladenosine (m(6)A) are likely distorted due to superimposed signals from saturated m(6)A residues. Here, we develop a neural network, DENA, for m(6)A quantification using t...

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Detalles Bibliográficos
Autores principales: Qin, Hang, Ou, Liang, Gao, Jian, Chen, Longxian, Wang, Jia-Wei, Hao, Pei, Li, Xuan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Method
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762864/
https://www.ncbi.nlm.nih.gov/pubmed/35039061
http://dx.doi.org/10.1186/s13059-021-02598-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8762864/
https://www.ncbi.nlm.nih.gov/pubmed/35039061
http://dx.doi.org/10.1186/s13059-021-02598-3

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