Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 170

The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.

Optical Multiplexed Bioassays for Improved Biomedical Diagnostics

Fan, Yong, Wang, Shangfeng, Zhang, Fan·2019·Angewandte Chemie International Edition

Abstract

Conventional analytical methods based on the detection of a single disease marker may not be sufficiently accurate because the progression of disease generally involves multiple chemicals and biomolecules. The drive for simultaneous analysis of multiple targets, which plays a key role in both basic biomedical research and clinical applications, demands the development of multiplexed bioassays with high‐throughput. In this minireview, we summarize the recent progress in optical multiplexed analytical techniques for improving biomedical diagnostics, in which fluorescence and surface enhanced Raman scattering (SERS) with distinctive optical features are chosen as the main readout signals. Focusing on multiplexed strategies in the biomedical field, a selection of recent contributions from biosensing of multiple analytes and multicolor cellular tracking to in vivo multiplexed bioimaging are highlighted. Finally, we frame the future challenges and opportunities for multiplexed bioanalysis.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/anie.201901964

Cites

5 of 5 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Show all 5 references

Cited by

See all 170

Metadata

Authors
Fan, Y., Wang, S., & Zhang, F.
Venue
Angewandte Chemie International Edition
Publisher
Wiley
Published
2019-07
Volume
58
Issue
38
Pages
13208-13219
ISSN
  • 1433-7851 (ISSN-L)
  • 1521-3773
OpenAlex
W2939959898
Cited by
170
References
5
FWCI
7.38
Type
journal article
Language
en
Open access
closed

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: Optical Multiplexed Bioassays for Improved Biomedical Diagnostics. https://app.cochat.ai/papers/10.1002/anie.201901964
The paper
Fan, Y., Wang, S., & Zhang, F. (2019). Optical Multiplexed Bioassays for Improved Biomedical Diagnostics. Angewandte Chemie International Edition. https://doi.org/10.1002/anie.201901964

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.