RGCNMDA: pathway-bridged relational graph learning with adaptive multi-view fusion for human miRNA-disease association prediction.

Hou C, Kone M, Xiang Y, Wang S

DOI: 10.1093/bioinformatics/btag620
Published: 2026 Aug 31
Container: Bioinformatics (Oxford, England)
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1093/bioinformatics/btag620,
  title = {RGCNMDA: pathway-bridged relational graph learning with adaptive multi-view fusion for human miRNA-disease association prediction.},
  author = {Hou C and Kone M and Xiang Y and Wang S},
  year = {2026},
  journal = {Bioinformatics (Oxford, England)},
  doi = {10.1093/bioinformatics/btag620},
  url = {https://doi.org/10.1093/bioinformatics/btag620}
}

RIS

TY  - JOUR
TI  - RGCNMDA: pathway-bridged relational graph learning with adaptive multi-view fusion for human miRNA-disease association prediction.
AU  - Hou C
AU  - Kone M
AU  - Xiang Y
AU  - Wang S
PY  - 2026
JO  - Bioinformatics (Oxford, England)
DO  - 10.1093/bioinformatics/btag620
UR  - https://doi.org/10.1093/bioinformatics/btag620
ER  -

APA

C, H., M, K., Y, X., & S, W. (2026). RGCNMDA: pathway-bridged relational graph learning with adaptive multi-view fusion for human miRNA-disease association prediction.. Bioinformatics (Oxford, England). https://doi.org/10.1093/bioinformatics/btag620

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pubmed · retrieved 2026-09-25T07:59:49.334Z