Evidence map›Paper›PMID 21967849›Full record

ReviewNucleic acids research2012

Luminescent detection of DNA-binding proteins.

Chung-Hang Leung, Daniel Shiu-Hin Chan, Hong-Zhang He, Zhen Cheng, Hui Yang, Dik-Lung Ma

Open access · goldAbstract readReview
In one paragraph

Review in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
4.3field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 97 citations in OpenAlex.

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  11. An Ir(III) complex chemosensor for the detection of thiols.Science and technology of advanced materials · 2016
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Chung-Hang LeungInstitute of Chinese Medical Sciences, University of Macau, Taipa, Macao, China. DuncanLeung@umac.mo
Daniel Shiu-Hin Chan
Hong-Zhang He
Zhen Cheng
Hui Yang
Dik-Lung Ma
Hong Kong Baptist University · HKUniversity of Macau · MO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcription factors play a central role in cell development, differentiation and growth in biological systems due to their ability to regulate gene expression by binding to specific DNA sequences within the nucleus. The dysregulation of transcription factor signaling has been implicated in the pathogenesis of a number of cancers, developmental disorders, inflammation and autoimmunity. There is thus a high demand for convenient high-throughput methodologies able to detect sequence-specific DNA-binding proteins and monitor their DNA-binding activities. Traditional approaches for protein detection include gel mobility shift assays, DNA footprinting and enzyme-linked immunosorbent assays (ELISAs) which tend to be tedious, time-consuming, and may necessitate the use of radiographic labeling. By contrast, luminescence technologies offer the potential for rapid, sensitive and low-cost detection that are amenable to high-throughput and real-time analysis. The discoveries of molecular beacons and aptamers have spear-headed the development of new luminescent methodologies for the detection of proteins over the last decade. We survey here recent advances in the development of luminescent detection methods for DNA-binding proteins, including those based on molecular beacons, aptamer beacons, label-free techniques and exonuclease protection.

Indexed as

Luminescent MeasurementsAptamers, NucleotideDNA-Binding ProteinsNuclease Protection AssaysOligonucleotide ProbesAptamers, NucleotideDNA-Binding ProteinsOligonucleotide Probes

Identifiers

PMID21967849
PMCPMC3273792
OpenAlexW2081784549

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.