Interpretable Deep Learning for Single-Molecule Nanopore Fingerprinting Using Physics-Guided Preprocessing
- DOI
- 10.1021/acssensors.5c04784
- Published
- 2026-02-20
- Container
- ACS Sensors
- Publisher
- American Chemical Society (ACS)
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1021/acssensors.5c04784,
title = {Interpretable Deep Learning for Single-Molecule Nanopore Fingerprinting Using Physics-Guided Preprocessing},
author = {Arjav Shah and Xin Kai Lee and Kun Li and Grant A. Knappe and Mark Bathe and George Barbastathis and Patrick S. Doyle},
year = {2026},
journal = {ACS Sensors},
doi = {10.1021/acssensors.5c04784},
url = {https://doi.org/10.1021/acssensors.5c04784}
}RIS
TY - JOUR TI - Interpretable Deep Learning for Single-Molecule Nanopore Fingerprinting Using Physics-Guided Preprocessing AU - Arjav Shah AU - Xin Kai Lee AU - Kun Li AU - Grant A. Knappe AU - Mark Bathe AU - George Barbastathis AU - Patrick S. Doyle PY - 2026 JO - ACS Sensors DO - 10.1021/acssensors.5c04784 UR - https://doi.org/10.1021/acssensors.5c04784 ER -
APA
Shah, A., Lee, X. K., Li, K., Knappe, G. A., Bathe, M., Barbastathis, G., & Doyle, P. S. (2026). Interpretable Deep Learning for Single-Molecule Nanopore Fingerprinting Using Physics-Guided Preprocessing. ACS Sensors. https://doi.org/10.1021/acssensors.5c04784
Source records
- crossref · retrieved 2026-09-27T12:09:13.651Z