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A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder.

Authors :
Wang Y
Pan Z
Mou M
Xia W
Zhang H
Zhang H
Liu J
Zheng L
Luo Y
Zheng H
Yu X
Lian X
Zeng Z
Li Z
Zhang B
Zheng M
Li H
Hou T
Zhu F
Source :
Nucleic acids research [Nucleic Acids Res] 2023 Nov 27; Vol. 51 (21), pp. e110.
Publication Year :
2023

Abstract

RNAs play essential roles in diverse physiological and pathological processes by interacting with other molecules (RNA/protein/compound), and various computational methods are available for identifying these interactions. However, the encoding features provided by existing methods are limited and the existing tools does not offer an effective way to integrate the interacting partners. In this study, a task-specific encoding algorithm for RNAs and RNA-associated interactions was therefore developed. This new algorithm was unique in (a) realizing comprehensive RNA feature encoding by introducing a great many of novel features and (b) enabling task-specific integration of interacting partners using convolutional autoencoder-directed feature embedding. Compared with existing methods/tools, this novel algorithm demonstrated superior performances in diverse benchmark testing studies. This algorithm together with its source code could be readily accessed by all user at: https://idrblab.org/corain/ and https://github.com/idrblab/corain/.<br /> (© The Author(s) 2023. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Details

Language :
English
ISSN :
1362-4962
Volume :
51
Issue :
21
Database :
MEDLINE
Journal :
Nucleic acids research
Publication Type :
Academic Journal
Accession number :
37889083
Full Text :
https://doi.org/10.1093/nar/gkad929