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A task-specific encoding algorithm for RNAs and RNA-associated interactions based on convolutional autoencoder
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DOI：10.1093/nar/gkad929.png)
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摘要
En 中文
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/. Graphical Abstract
Keyword:
WEB SERVER
SEQUENCE
MIRNA
PROTEINS
DATABASE
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期刊
IF:
13.1
论文数:
3.6W
被引数:
29.0W
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引用论文
iLearn: an integrated platform and meta-learner for feature engineering, machine-learning analysis and modeling of DNA, RNA and protein sequence dataiLearn: 用于DNA，RNA和蛋白质序列数据的特征工程，机器学习分析和建模的集成平台和元学习器
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