Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 178

The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.

The BRET technology and its application to screening assays

Bacart, Johan, Corbel, Caroline, Jockers, Ralf, Bach, Stéphane, Couturier, Cyril·2008·Biotechnology Journal

Abstract

The bioluminescence resonance energy transfer (BRET) method is based on resonance energy transfer between a light‐emitting enzyme and a fluorescent acceptor. Since its first description in 1999, several versions of BRET have been described using different substrates and energy donor/acceptor couples. Today, BRET is considered as one of the most versatile techniques for studying the dynamics of protein‐protein interactions in living cells. Various studies have applied BRET‐based assays to screen new receptor ligands and inhibitors of disease‐related‐proteases. Inhibitors of protein‐protein interactions are likely to become a new major class of therapeutic drugs, and BRET technology is expected to play an important role in the identification of such compounds. This review describes the original BRET‐based methodology, more recent variants, and potential applications to drug screening.

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/biot.200700222

Cites

6 of 6 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 6 references

Cited by

See all 178

Metadata

Authors
Bacart, J., Corbel, C., Jockers, R., Bach, S., & Couturier, C.
Venue
Biotechnology Journal
Publisher
Wiley
Published
2008-03
Volume
3
Issue
3
Pages
311-324
ISSN
  • 1860-6768 (ISSN-L)
  • 1860-7314
OpenAlex
W2147476348
Cited by
178
References
6
FWCI
4.47
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: The BRET technology and its application to screening assays. https://app.cochat.ai/papers/10.1002/biot.200700222
The paper
Bacart, J., Corbel, C., Jockers, R., Bach, S., & Couturier, C. (2008). The BRET technology and its application to screening assays. Biotechnology Journal. https://doi.org/10.1002/biot.200700222

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.