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

2021-12-30

Abstract excerpt

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 the sequencing data of in vivo transcripts from Arabidopsis. DENA identifies 90% of miCLIP-detected m 6 A si...

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Literature Corpus work: 60a5ce3a-51c4-53d0-a62c-660375e9093b
DOI: 10.1101/2021.12.29.474495

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DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N 6 -methyladenosine on RNADOI 10.1101/2021.12.29.474495Read

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DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of <i>N</i> <sup>6</sup> -methyladenosine on RNA

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