The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.
Nanoscopic Porous Sensors
Abstract
There are thousands of different nanometer-scale pores in biology, many of which act as sensors for specific chemical agents. Recent work suggests that protein and solid-state nanopores have many potential uses in a wide variety of analytical applications. In this review we survey this field of research and discuss the prospects for advances that could be made in the near future.
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Citations
Cites
A tutorial on hidden Markov models and selected applications in speech recognition
Rabiner, L. R. (1989) · Proceedings of the IEEE · doi:10.1109/5.18626 · Cited by 22,743
An introduction to hidden Markov models
Rabiner, L., & Juang, B. (1986) · IEEE ASSP Magazine · doi:10.1109/massp.1986.1165342 · Cited by 4,775
Cited by
Perspective and Prospectus on Single-Entity Electrochemistry
Baker, L. A. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.8b09747 · Cited by 285
Metadata
- Authors
- Kasianowicz, J. J., Robertson, J. W. F., Chan, E. R., Reiner, J. E., & Stanford, V. M.
- Venue
- Annual Review of Analytical Chemistry
- Publisher
- Annual Reviews
- Published
- 2008-07-01
- Volume
- 1
- Issue
- 1
- Pages
- 737-766
- ISSN
- 1936-1327 (ISSN-L)
- 1936-1335
- OpenAlex
- W2129234254
- Cited by
- 284
- References
- 2
- FWCI
- 1.00
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: Nanoscopic Porous Sensors. https://app.cochat.ai/papers/10.1146/annurev.anchem.1.031207.112818
- The paper
- Kasianowicz, J. J., Robertson, J. W. F., Chan, E. R., Reiner, J. E., & Stanford, V. M. (2008). Nanoscopic Porous Sensors. Annual Review of Analytical Chemistry. https://doi.org/10.1146/annurev.anchem.1.031207.112818
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
