Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges.
- DOI
- 10.1109/mnano.2023.3262099
- Published
- 2023 Jun
- Container
- IEEE nanotechnology magazine
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.1109/mnano.2023.3262099,
title = {Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges.},
author = {Balasubramaniam S and Somathilaka S and Sun S and Ratwatte A and Pierobon M},
year = {2023},
journal = {IEEE nanotechnology magazine},
doi = {10.1109/mnano.2023.3262099},
url = {https://doi.org/10.1109/mnano.2023.3262099}
}RIS
TY - JOUR TI - Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges. AU - Balasubramaniam S AU - Somathilaka S AU - Sun S AU - Ratwatte A AU - Pierobon M PY - 2023 JO - IEEE nanotechnology magazine DO - 10.1109/mnano.2023.3262099 UR - https://doi.org/10.1109/mnano.2023.3262099 ER -
APA
S, B., S, S., S, S., A, R., & M, P. (2023). Realizing Molecular Machine Learning through Communications for Biological AI: Future Directions and Challenges.. IEEE nanotechnology magazine. https://doi.org/10.1109/mnano.2023.3262099
Source records
- pubmed · retrieved 2026-09-25T18:16:27.808Z