Complementary feature learning across multiple heterogeneous networks and multimodal attribute learning for predicting disease-related miRNAs
Summary: Inferring the latent disease-related miRNAs is helpful for providing a deep insight into observing the disease pathogenesis. We propose a method, CMMDA, to encode and integrate the context relationship among multiple heterogeneous networks, the complementary information across these network...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Elsevier
2024-02-01
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Series: | iScience |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S2589004223027165 |