Geometric deep reinforcement learning with hierarchical variational autoencoders for de novo drug design and activity optimization.

Murala DK

DOI: 10.1007/s10822-026-00812-7
Published: 2026 May 4
Container: Journal of computer-aided molecular design
Publisher: Not recorded
Open access: unknown

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Cite this work

BibTeX

@article{allodium:10.1007/s10822-026-00812-7,
  title = {Geometric deep reinforcement learning with hierarchical variational autoencoders for de novo drug design and activity optimization.},
  author = {Murala DK},
  year = {2026},
  journal = {Journal of computer-aided molecular design},
  doi = {10.1007/s10822-026-00812-7},
  url = {https://doi.org/10.1007/s10822-026-00812-7}
}

RIS

TY  - JOUR
TI  - Geometric deep reinforcement learning with hierarchical variational autoencoders for de novo drug design and activity optimization.
AU  - Murala DK
PY  - 2026
JO  - Journal of computer-aided molecular design
DO  - 10.1007/s10822-026-00812-7
UR  - https://doi.org/10.1007/s10822-026-00812-7
ER  -

APA

DK, M. (2026). Geometric deep reinforcement learning with hierarchical variational autoencoders for de novo drug design and activity optimization.. Journal of computer-aided molecular design. https://doi.org/10.1007/s10822-026-00812-7

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pubmed · retrieved 2026-09-25T19:37:46.343Z