Evidence map›Paper›PMID 21347314›Full record

ArticlePLoS computational biology2011

De-novo discovery of differentially abundant transcription factor binding sites including their positional preference.

Jens Keilwagen, Jan Grau, Ivan A Paponov, Stefan Posch, Marc Strickert, Ivo Grosse

Erratum issuedAbstract readEvaluation Study
In one paragraph

Article in PLoS computational biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Transcription Factors in Plant Gene Expression Regulation.International journal of molecular sciences · 2025
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  4. Methyl Jasmonate Activates theMolecules (Basel, Switzerland) · 2022
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4 · The record

Corrections and comments

  • Erratum issued
5 · Who and what money

Authors and funding

6 authors.

Jens KeilwagenMolecular Genetics, Leibniz Institute of Plant Genetics and Crop Plant Research (IPK), Gatersleben, Germany. Jens.Keilwagen@ipk-gatersleben.de
Jan Grau
Ivan A Paponov
Stefan Posch
Marc Strickert
Ivo Grosse

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Transcription factors are a main component of gene regulation as they activate or repress gene expression by binding to specific binding sites in promoters. The de-novo discovery of transcription factor binding sites in target regions obtained by wet-lab experiments is a challenging problem in computational biology, which has not been fully solved yet. Here, we present a de-novo motif discovery tool called Dispom for finding differentially abundant transcription factor binding sites that models existing positional preferences of binding sites and adjusts the length of the motif in the learning process. Evaluating Dispom, we find that its prediction performance is superior to existing tools for de-novo motif discovery for 18 benchmark data sets with planted binding sites, and for a metazoan compendium based on experimental data from micro-array, ChIP-chip, ChIP-DSL, and DamID as well as Gene Ontology data. Finally, we apply Dispom to find binding sites differentially abundant in promoters of auxin-responsive genes extracted from Arabidopsis thaliana microarray data, and we find a motif that can be interpreted as a refined auxin responsive element predominately positioned in the 250-bp region upstream of the transcription start site. Using an independent data set of auxin-responsive genes, we find in genome-wide predictions that the refined motif is more specific for auxin-responsive genes than the canonical auxin-responsive element. In general, Dispom can be used to find differentially abundant motifs in sequences of any origin. However, the positional distribution learned by Dispom is especially beneficial if all sequences are aligned to some anchor point like the transcription start site in case of promoter sequences. We demonstrate that the combination of searching for differentially abundant motifs and inferring a position distribution from the data is beneficial for de-novo motif discovery. Hence, we make the tool freely available as a component of the open-source Java framework Jstacs and as a stand-alone application at http://www.jstacs.de/index.php/Dispom.

Indexed as

AnimalsArabidopsisArabidopsis ProteinsBinding SitesComputational BiologyDatabases, GeneticDNA, PlantGenes, PlantHumansIndoleacetic AcidsModels, GeneticModels, StatisticalPromoter Regions, GeneticTranscription FactorsArabidopsis ProteinsDNA, PlantIndoleacetic AcidsTranscription Factors

Identifiers

PMID21347314
PMCPMC3037384

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.