The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Single‐Molecule Sensors: Challenges and Opportunities for Quantitative Analysis
Open accessAbstract
Measurement science has been converging to smaller and smaller samples, such that it is now possible to detect single molecules. This Review focuses on the next generation of analytical tools that combine single‐molecule detection with the ability to measure many single molecules simultaneously and/or process larger and more complex samples. Such single‐molecule sensors constitute a new type of quantitative analytical tool, as they perform analysis by molecular counting and thus potentially capture the heterogeneity of the sample. This Review outlines the advantages and potential of these new, quantitative single‐molecule sensors, the measurement challenges in making single‐molecule devices suitable for analysis, the inspiration biology provides for overcoming these challenges, and some of the solutions currently being explored.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Direct observation of kinesin stepping by optical trapping interferometry
Svoboda, K., Schmidt, C. F., Schnapp, B. J., & Block, S. M. (1993) · Nature · doi:10.1038/365721a0 · Cited by 1,910
Du, W., Li, L., Nichols, K. P., & Ismagilov, R. F. (2009) · Lab on a Chip · doi:10.1039/b908978k · Cited by 351
Shen, F., Davydova, E. K., Du, W., Kreutz, J. E., Piepenburg, O., & Ismagilov, R. F. (2011) · Analytical Chemistry · doi:10.1021/ac200247e · Cited by 240
Conditional density-based analysis of T cell signaling in single-cell data
Krishnaswamy, S., Spitzer, M. H., Mingueneau, M., Bendall, S. C., Litvin, O., Stone, E., Pe’er, D., & Nolan, G. P. (2014) · Science · doi:10.1126/science.1250689 · Cited by 225
Ras activation by SOS: Allosteric regulation by altered fluctuation dynamics
Iversen, L., Tu, H.-L., Lin, W.-C., Christensen, S. M., Abel, S. M., Iwig, J., Wu, H.-J., Gureasko, J., Rhodes, C., Petit, R. S., et al. (2014) · Science · doi:10.1126/science.1250373 · Cited by 154
Cited by
Single-Molecule Plasmon Sensing: Current Status and Future Prospects
Taylor, A. B., & Zijlstra, P. (2017) · ACS Sensors · doi:10.1021/acssensors.7b00382 · Cited by 366
Single Biomolecule Imaging by Electrochemiluminescence
Liu, Y., Zhang, H., Li, B., Liu, J., Jiang, D., Liu, B., & Sojic, N. (2021) · Journal of the American Chemical Society · doi:10.1021/jacs.1c06673 · Cited by 303
Nanoparticles for super-resolution microscopy and single-molecule tracking
Jin, D., Xi, P., Wang, B., Zhang, L., Enderlein, J., & van Oijen, A. M. (2018) · Nature Methods · doi:10.1038/s41592-018-0012-4 · Cited by 283
Single-molecule protein sensing in a nanopore: a tutorial
Varongchayakul, N., Song, J., Meller, A., & Grinstaff, M. W. (2018) · Chemical Society Reviews · doi:10.1039/c8cs00106e · Cited by 282
Single-molecule detection with a millimetre-sized transistor
Macchia, E., Manoli, K., Holzer, B., Di Franco, C., Ghittorelli, M., Torricelli, F., Alberga, D., Mangiatordi, G. F., Palazzo, G., Scamarcio, G., et al. (2018) · Nature Communications · doi:10.1038/s41467-018-05235-z · Cited by 253
Metadata
- Authors
- Gooding, J. J., & Gaus, K.
- Venue
- Angewandte Chemie International Edition
- Publisher
- Wiley
- Published
- 2016-07-22
- Volume
- 55
- Issue
- 38
- Pages
- 11354-11366
- ISSN
- 1433-7851 (ISSN-L)
- 1521-3773
- OpenAlex
- W2490860910
- Cited by
- 340
- References
- 5
- FWCI
- 15.12
- Type
- journal article
- Language
- en
- Open access
- bronze
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Single‐Molecule Sensors: Challenges and Opportunities for Quantitative Analysis. https://app.cochat.ai/papers/10.1002/anie.201600495
- The paper
- Gooding, J. J., & Gaus, K. (2016). Single‐Molecule Sensors: Challenges and Opportunities for Quantitative Analysis. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201600495
Data sources
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.