Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges

Yang, Sumin; Kim, Sung-Hyun; Kang, Min-Hee; Joo, Jae‐Yeol

doi:10.1007/s12272-023-01450-5

Arch. Pharm. Res.

2023

DOI: 10.1007/s12272-023-01450-5

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Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges

Sumin Yang

Sung-Hyun Kim

Min-Hee Kang

et al.

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Cited by 2 publications

References 130 publications

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Molecular insights into regulatory RNAs in the cellular machinery

Yang,

Kim,

Yang

et al. 2024

Exp Mol Med

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It is apparent that various functional units within the cellular machinery are derived from RNAs. The evolution of sequencing techniques has resulted in significant insights into approaches for transcriptome studies. Organisms utilize RNA to govern cellular systems, and a heterogeneous class of RNAs is involved in regulatory functions. In particular, regulatory RNAs are increasingly recognized to participate in intricately functioning machinery across almost all levels of biological systems. These systems include those mediating chromatin arrangement, transcription, suborganelle stabilization, and posttranscriptional modifications. Any class of RNA exhibiting regulatory activity can be termed a class of regulatory RNA and is typically represented by noncoding RNAs, which constitute a substantial portion of the genome. These RNAs function based on the principle of structural changes through cis and/or trans regulation to facilitate mutual RNA‒RNA, RNA‒DNA, and RNA‒protein interactions. It has not been clearly elucidated whether regulatory RNAs identified through deep sequencing actually function in the anticipated mechanisms. This review addresses the dominant properties of regulatory RNAs at various layers of the cellular machinery and covers regulatory activities, structural dynamics, modifications, associated molecules, and further challenges related to therapeutics and deep learning.

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Molecular insights into regulatory RNAs in the cellular machinery

Yang,

Kim,

Yang

et al. 2024

Exp Mol Med

Self Cite

View full text Add to dashboard Cite

show abstract

Potent of strategic approaches for tauopathies ranging from single-cell transcriptome to microbiome

Kim,

Yang,

Yang

et al. 2023

Animal Cells and Systems

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Harnessing deep learning into hidden mutations of neurological disorders for therapeutic challenges

Cited by 2 publications

References 130 publications

Molecular insights into regulatory RNAs in the cellular machinery

Molecular insights into regulatory RNAs in the cellular machinery

Potent of strategic approaches for tauopathies ranging from single-cell transcriptome to microbiome

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