Evidence map›Paper›PMID 15942028›Full record

ArticleNucleic acids research2005

A universally applicable method of operon map prediction on minimally annotated genomes using conserved genomic context.

Martin T Edwards, Stuart C G Rison, Neil G Stoker, Lorenz Wernisch

Open access · goldAbstract readEvaluation Study
In one paragraph

Article in Nucleic acids research, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.9field-weighted citation impact, top 15% 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

18 citing papers in PubMed, 88 citations in OpenAlex.

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  17. Operon prediction in Pyrococcus furiosus.Nucleic acids research · 2007
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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

4 authors at 1 institution in 1 country.

Martin T EdwardsSchool of Crystallography, Birkbeck College London WC1E 7HX, UK. m.edwards@mail.cryst.bbk.ac.uk
Stuart C G Rison
Neil G Stoker
Lorenz Wernisch
Birkbeck, University of London · GB

Funding

Wellcome Trust
6 · The paper itself

Abstract

An important step in understanding the regulation of a prokaryotic genome is the generation of its transcription unit map. The current strongest operon predictor depends on the distributions of intergenic distances (IGD) separating adjacent genes within and between operons. Unfortunately, experimental data on these distance distributions are limited to Escherichia coli and Bacillus subtilis. We suggest a new graph algorithmic approach based on comparative genomics to identify clusters of conserved genes independent of IGD and conservation of gene order. As a consequence, distance distributions of operon pairs for any arbitrary prokaryotic genome can be inferred. For E.coli, the algorithm predicts 854 conserved adjacent pairs with a precision of 85%. The IGD distribution for these pairs is virtually identical to the E.coli operon pair distribution. Statistical analysis of the predicted pair IGD distribution allows estimation of a genome-specific operon IGD cut-off, obviating the requirement for a training set in IGD-based operon prediction. We apply the method to a representative set of eight genomes, and show that these genome-specific IGD distributions differ considerably from each other and from the distribution in E.coli.

Indexed as

OperonAlgorithmsBase SequenceChromosome MappingConserved SequenceEscherichia coliGenome, BacterialGenomics

Identifiers

PMID15942028
PMCPMC1143694
OpenAlexW2132867976

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.