MTAGCN: predicting miRNA-target associations in Camellia sinensis var. assamica through graph convolution neural network

MTAGCN: predicting miRNA-target associations in Camellia sinensis var. assamica through graph convolution neural network

Abstract Background MircoRNAs (miRNAs) play a central role in diverse biological processes of Camellia sinensis var.assamica (CSA) through their associations with target mRNAs, including CSA growth, development and stress response. However, although the experiment methods of CSA miRNA-target identif...

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Bibliographic Details
Main Authors: Haisong Feng, Ying Xiang, Xiaosong Wang, Wei Xue, Zhenyu Yue
Format: Article
Language:English
Published: BMC 2022-07-01
Series:BMC Bioinformatics
Subjects:
CSA miRNA-target association prediction
Deep learning
Graph convolution network
Layer attention mechanism
Online Access:https://doi.org/10.1186/s12859-022-04819-3

Internet

https://doi.org/10.1186/s12859-022-04819-3

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