Skip to main content
Fig. 2 | BMC Genomics

Fig. 2

From: GDCL-NcDA: identifying non-coding RNA-disease associations via contrastive learning between deep graph learning and deep matrix factorization

Fig. 2

An illustration of the GDCL-NcDA framework. \(\textbf{A}\) The multi-source deep graph learning is to obtain significance within similarity network and encode every similarity network. \(\textbf{B}\) The multichannel attention mechanism is performed to obtain significance among diverse similarity networks. The reconstruction of association graph (matrix) for downstream predictive task. \(\textbf{C}\) The DMF for final identification task based on reformulated association score matrix. The contrastive loss generated on the reconstructed graph and predicted graph

Back to article page

BMC Genomics

ISSN: 1471-2164

Contact us