KAN-GIN: Adaptive Nonlinear Molecular Representation Learning for Drug-Target Affinity Prediction.

Bedoui A, Duraisamy N, Cherkaoui M

Open source

DOI
10.3390/ph19091458
Published
2026 Sep 14
Container
Pharmaceuticals (Basel, Switzerland)
Publisher
Not recorded
Open access
unknown

Credibility signals

limited evidence Score 43/100 under policy 1.0.0. This is a metadata assessment, not a judgment of the paper's conclusions.

Show all credibility signals

Cite this work

BibTeX

@article{allodium:10.3390/ph19091458,
  title = {KAN-GIN: Adaptive Nonlinear Molecular Representation Learning for Drug-Target Affinity Prediction.},
  author = {Bedoui A and Duraisamy N and Cherkaoui M},
  year = {2026},
  journal = {Pharmaceuticals (Basel, Switzerland)},
  doi = {10.3390/ph19091458},
  url = {https://doi.org/10.3390/ph19091458}
}

RIS

TY  - JOUR
TI  - KAN-GIN: Adaptive Nonlinear Molecular Representation Learning for Drug-Target Affinity Prediction.
AU  - Bedoui A
AU  - Duraisamy N
AU  - Cherkaoui M
PY  - 2026
JO  - Pharmaceuticals (Basel, Switzerland)
DO  - 10.3390/ph19091458
UR  - https://doi.org/10.3390/ph19091458
ER  - 

APA

A, B., N, D., & M, C. (2026). KAN-GIN: Adaptive Nonlinear Molecular Representation Learning for Drug-Target Affinity Prediction.. Pharmaceuticals (Basel, Switzerland). https://doi.org/10.3390/ph19091458

Source records