Evidence map›Paper›PMID 17014715›Full record

ArticleBMC bioinformatics2006

Detection of prokaryotic promoters from the genomic distribution of hexanucleotide pairs.

Pierre-Etienne Jacques, Sébastien Rodrigue, Luc Gaudreau, Jean Goulet, Ryszard Brzezinski

Open access · goldAbstract readComparative StudyValidation Study
In one paragraph

Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
1.2field-weighted citation impact, top 22% 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

10 citing papers in PubMed, 32 citations in OpenAlex.

  1. The σScientific reports · 2021
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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

5 authors at 1 institution in 1 country.

Pierre-Etienne JacquesDépartement de biologie, Université de Sherbrooke, Sherbrooke, Québec, Canada. Pierre-Etienne.Jacques@USherbrooke.ca
Sébastien Rodrigue
Luc Gaudreau
Jean Goulet
Ryszard Brzezinski
Université de Sherbrooke · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn bacteria, sigma factors and other transcriptional regulatory proteins recognize DNA patterns upstream of their target genes and interact with RNA polymerase to control transcription. As a consequence of evolution, DNA sequences recognized by transcription factors are thought to be enriched in intergenic regions (IRs) and depleted from coding regions of prokaryotic genomes.

resultsIn this work, we report that genomic distribution of transcription factors binding sites is biased towards IRs, and that this bias is conserved amongst bacterial species. We further take advantage of this observation to develop an algorithm that can efficiently identify promoter boxes by a distribution-dependent approach rather than a direct sequence comparison approach. This strategy, which can easily be combined with other methodologies, allowed the identification of promoter sequences in ten species and can be used with any annotated bacterial genome, with results that rival with current methodologies. Experimental validations of predicted promoters also support our approach.

conclusionConsidering that complete genomic sequences of over 1000 bacteria will soon be available and that little transcriptional information is available for most of them, our algorithm constitutes a promising tool for the prediction of promoter sequences. Importantly, our methodology could also be adapted to identify DNA sequences recognized by other regulatory proteins.

Indexed as

AlgorithmsBase SequenceGenome, BacterialMolecular Sequence DataProkaryotic Initiation FactorsPromoter Regions, GeneticSequence AnalysisTranscription, GeneticProkaryotic Initiation Factors

Identifiers

PMID17014715
PMCPMC1615881
OpenAlexW2111492198

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.