Dual graph convolutional neural network for predicting chemical networks

Dual graph convolutional neural network for predicting chemical networks

Abstract Background Predicting of chemical compounds is one of the fundamental tasks in bioinformatics and chemoinformatics, because it contributes to various applications in metabolic engineering and drug discovery. The recent rapid growth of the amount of available data has enabled applications of...

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Bibliographic Details
Main Authors: Shonosuke Harada, Hirotaka Akita, Masashi Tsubaki, Yukino Baba, Ichigaku Takigawa, Yoshihiro Yamanishi, Hisashi Kashima
Format: Article
Language:English
Published: BMC 2020-04-01
Series:BMC Bioinformatics
Subjects:
Chemical network prediction
Graph convolutional neural network
Graph of graphs
Online Access:http://link.springer.com/article/10.1186/s12859-020-3378-0

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http://link.springer.com/article/10.1186/s12859-020-3378-0

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