Peer-reviewedCC BY-NC-NDJournal of pharmaceutical analysis1 Jun 2026

ACAP-AG: A graph neural network model for anticancer activity prediction by integrating heterogeneous data.

Yong-Cui Wang¹
Min-Min Hu^1,2,3
Tian-Ze Li¹
Sheng-Zhen Li^1,3
Ji-Jun Chen^1,3

¹Kunming Institute of Botany, Chinese Academy of Sciences, State Key Laboratory of Phytochemistry and Natural Medicines, Kunming, 650201, China.
²Department of Special Wards Branch, The Second Affiliated Hospital of Kunming Medical University, Kunming, 650101, China.
³University of Chinese Academy of Sciences, Beijing, 100049, China.

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Cite

BibTeX

@article{wang2026acapag,
  title = {{ACAP-AG: A graph neural network model for anticancer activity prediction by integrating heterogeneous data.}},
  author = {Yong-Cui Wang and Min-Min Hu and Tian-Ze Li and Sheng-Zhen Li and Ji-Jun Chen},
  journal = {Journal of pharmaceutical analysis},
  year = {2026},
  month = jun,
  doi = {10.1016/j.jpha.2026.101680},
  url = {https://europepmc.org/article/MED/42999687},
  note = {CC BY-NC-ND},
}

RIS

TY  - JOUR
TI  - ACAP-AG: A graph neural network model for anticancer activity prediction by integrating heterogeneous data.
AU  - Yong-Cui Wang
AU  - Min-Min Hu
AU  - Tian-Ze Li
AU  - Sheng-Zhen Li
AU  - Ji-Jun Chen
PY  - 2026
DA  - 2026/06/01
JO  - Journal of pharmaceutical analysis
DO  - 10.1016/j.jpha.2026.101680
UR  - https://europepmc.org/article/MED/42999687
SN  - 2095-1779
SN  - 2214-0883
ER  -

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