Evidence map›Paper›PMID 16970547›Full record

ArticleGenomics, proteomics & bioinformatics2006

Characterization of binding sites of eukaryotic transcription factors.

Jiang Qian, Jimmy Lin, Donald J Zack

Open access · goldAbstract readComparative Study
In one paragraph

Article in Genomics, proteomics & bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 88% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. 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

3 authors at 2 institutions in 1 country.

Jiang QianThe Wilmer Institute, Johns Hopkins University School of Medicine, Baltimore, MD 21287, USA. jiang.qian@jhmi.edu
Jimmy Lin
Donald J Zack
Johns Hopkins University · USJohns Hopkins Medicine · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

To explore the nature of eukaryotic transcription factor (TF) binding sites and determine how they differ from surrounding DNA sequences, we examined four features associated with DNA-binding sites: G+C content, pattern complexity, palindromic structure, and Markov sequence ordering. Our analysis of the regulatory motifs obtained from the TRANSFAC database, using yeast intergenic sequences as background, revealed that these four features show variable enrichment in motif sequences. For example, motif sequences were more likely to have palindromic structure than were background sequences. In addition, these features were tightly localized to the regulatory motifs, indicating that they are a property of the motif sequences themselves and are not shared by the general promoter "environment" in which the regulatory motifs reside. By breaking down the motif sequences according to the TF classes to which they bind, more specific associations were identified. Finally, we found that some correlations, such as G+C content enrichment, were species-specific, while others, such as complexity enrichment, were universal across the species examined. The quantitative analysis provided here should increase our understanding of protein-DNA interactions and also help facilitate the discovery of regulatory motifs through bioinformatics.

Indexed as

Sequence Analysis, DNAAnimalsBase CompositionBinding SitesDatabases, Nucleic AcidDatabases, ProteinDNA, FungalHumansMiceProtein BindingResponse ElementsSaccharomyces cerevisiaeSaccharomyces cerevisiae ProteinsSpecies SpecificityTranscription FactorsZinc FingersDNA, FungalSaccharomyces cerevisiae ProteinsTranscription Factors

Identifiers

PMID16970547
PMCPMC5054036
OpenAlexW2074581987

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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.