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Identification of microbe-disease signed associations via multi-scale variational graph autoencoder based on signed message propagation.

Huan ZhuHongxia HaoLiang Yu
Published in: BMC biology (2024)
MSignVGAE achieves AUROC and AUPR values of 0.9742 and 0.9601, respectively. Case studies on three diseases demonstrate that MSignVGAE can effectively capture a comprehensive distribution of associations by leveraging signed information.
Keyphrases
  • healthcare
  • health information
  • bioinformatics analysis