AIMC Topic: RNA Methylation

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Quantitative profiling N1-methyladenosine (m1A) RNA methylation from Oxford nanopore direct RNA sequencing data.

Methods (San Diego, Calif.) May 18, 2024
With the recent advanced direct RNA sequencing technique that proposed by the Oxford Nanopore Technologies, RNA modifications can be detected and profiled in a simple and straightforward manner. Majority nanopore-based modification studies were devot...
Humans Machine Learning Algorithms Sequence Analysis, RNA Workflow RNA Methylation HEK293 Cells Adenosine RNA Processing, Post-Transcriptional Nanopore Sequencing RNA Methylation
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Interpretable Multi-Scale Deep Learning for RNA Methylation Analysis across Multiple Species.

International journal of molecular sciences Mar 1, 2024
RNA modification plays a crucial role in cellular regulation. However, traditional high-throughput sequencing methods for elucidating their functional mechanisms are time-consuming and labor-intensive, despite extensive research. Moreover, existing m...
Deep Learning Protein Processing, Post-Translational RNA Methylation RNA Methylation
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