Evidence map›Paper›PMID 12907741›Full record

ArticleNucleic acids research2003

Gene expression analysis using single molecule detection.

Kerstin Korn, Paola Gardellin, Bohao Liao, Mario Amacker, Asa Bergström, Henrik Björkman, Agnès Camacho, Sabine Dörhöfer, Klaus Dörre, Johanna Enström and 10 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–field-weighted citation impact
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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
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  5. Article
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

20 authors.

Kerstin KornGnothis AB, Electrum 212, SE-164 40 Kista, Sweden.
Paola Gardellin
Bohao Liao
Mario Amacker
Asa Bergström
Henrik Björkman
Agnès Camacho
Sabine Dörhöfer
Klaus Dörre
Johanna Enström
Thomas Ericson
Tatiana Favez
Michael Gösch
Adrian Honegger
Sandra Jaccoud
Markus Lapczyna
Erik Litborn
Per Thyberg
Holger Winter
Rudolf Rigler

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent developments of single molecule detection techniques and in particular the introduction of fluorescence correlation spectroscopy (FCS) led to a number of important applications in biological research. We present a unique approach for the gene expression analysis using dual-color cross-correlation. The expression assay is based on gene-specific hybridization of two dye-labeled DNA probes to a selected target gene. The counting of the dual-labeled molecules within the solution allows the quantification of the expressed gene copies in absolute numbers. As detection and analysis by FCS can be performed at the level of single molecules, there is no need for any type of amplification. We describe the gene expression assay and present data demonstrating the capacity of this novel technology. In order to prove the gene specificity, we performed experiments with gene-depleted total cDNA. The biological application was demonstrated by quantifying selected high, medium and low abundant genes in cDNA prepared from HL-60 cells.

Indexed as

Gene ExpressionActinsAlgorithmsCarbocyaninesDNA-Binding ProteinsDNA, ComplementaryFluorescent DyesHL-60 CellsHumansK562 CellsNF-kappa BOligonucleotide ProbesPeptide Elongation Factor 1Phosphoglycerate Kinaserab1 GTP-Binding ProteinsRhodaminesActinsCarbocyaninescyanine dye 5DNA-Binding ProteinsDNA, ComplementaryFluorescent DyesNF-kappa BOligonucleotide ProbesPeptide Elongation Factor 1Phosphoglycerate Kinaserab1 GTP-Binding ProteinsRhodaminesRibosomal Proteinsribosomal protein S19Transcription Factor RelATubulin

Identifiers

PMID12907741
PMCPMC169981

What OpenQuestion holds

Textmetadata
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.