Dockformer: A Transformer-Based Molecular Docking Paradigm for Large-Scale Virtual Screening.
- DOI
- 10.1109/tnnls.2026.3725736
- Published
- 2026 Aug 28
- Container
- IEEE transactions on neural networks and learning systems
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1109/tnnls.2026.3725736,
title = {Dockformer: A Transformer-Based Molecular Docking Paradigm for Large-Scale Virtual Screening.},
author = {Yang Z and Ji J and He S and Li J and He T and Bai R and Zhu Z and Ong YS},
year = {2026},
journal = {IEEE transactions on neural networks and learning systems},
doi = {10.1109/tnnls.2026.3725736},
url = {https://doi.org/10.1109/tnnls.2026.3725736}
}RIS
TY - JOUR TI - Dockformer: A Transformer-Based Molecular Docking Paradigm for Large-Scale Virtual Screening. AU - Yang Z AU - Ji J AU - He S AU - Li J AU - He T AU - Bai R AU - Zhu Z AU - Ong YS PY - 2026 JO - IEEE transactions on neural networks and learning systems DO - 10.1109/tnnls.2026.3725736 UR - https://doi.org/10.1109/tnnls.2026.3725736 ER -
APA
Z, Y., J, J., S, H., J, L., T, H., R, B., Z, Z., & YS, O. (2026). Dockformer: A Transformer-Based Molecular Docking Paradigm for Large-Scale Virtual Screening.. IEEE transactions on neural networks and learning systems. https://doi.org/10.1109/tnnls.2026.3725736
Source records
- pubmed · retrieved 2026-09-26T05:23:30.596Z