Evidence map›Paper›PMID 18718942›Full record

ArticleBioinformatics (Oxford, England)2008

Seeder: discriminative seeding DNA motif discovery.

François Fauteux, Mathieu Blanchette, Martina V Strömvik

Open access · hybridAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing papers in PubMed
2.1field-weighted citation impact, top 13% 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

22 citing papers in PubMed, 48 citations in OpenAlex.

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  17. DECOD: fast and accurate discriminative DNA motif finding.Bioinformatics (Oxford, England) · 2011
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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

3 authors at 1 institution in 1 country.

François FauteuxDepartment of Plant Science, McGill University, Ste-Anne-de-Bellevue, Quebec, Canada.
Mathieu Blanchette
Martina V Strömvik
McGill University · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

motivationThe computational identification of transcription factor binding sites is a major challenge in bioinformatics and an important complement to experimental approaches.

resultsWe describe a novel, exact discriminative seeding DNA motif discovery algorithm designed for fast and reliable prediction of cis-regulatory elements in eukaryotic promoters. The algorithm is tested on biological benchmark data and shown to perform equally or better than other motif discovery tools. The algorithm is applied to the analysis of plant tissue-specific promoter sequences and successfully identifies key regulatory elements.

Indexed as

AlgorithmsRegulatory Elements, TranscriptionalSequence Analysis, DNAAnimalsArabidopsisBase SequenceBinding SitesComputational BiologyHumansMolecular Sequence DataPromoter Regions, GeneticTranscription FactorsTranscription Factors

Identifiers

PMID18718942
PMCPMC2562012
OpenAlexW2156733952

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.