DANE-MDA: Predicting microRNA-disease associations via deep attributed network embedding.
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ABSTRACT:
SUBMITTER: Ji BY
PROVIDER: S-EPMC8141887 | biostudies-literature | 2021 Jun
REPOSITORIES: biostudies-literature
Publications
DANE-MDA: Predicting microRNA-disease associations via deep attributed network embedding.
Ji Bo-Ya BY You Zhu-Hong ZH Wang Yi Y Li Zheng-Wei ZW Wong Leon L
iScience 20210420 6
Predicting the microRNA-disease associations by using computational methods is conductive to the efficiency of costly and laborious traditional bio-experiments. In this study, we propose a computational machine learning-based method (DANE-MDA) that preserves integrated structure and attribute features via deep attributed network embedding to predict potential miRNA-disease associations. Specifically, the integrated features are extracted by using deep stacked auto-encoder on the diverse orders o ...[more]
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