Evidence map›Paper›PMID 14500844›Full record

ArticleNucleic acids research2003

A non-parametric model for transcription factor binding sites.

Oliver D King, Frederick P Roth

Abstract readComparative StudyEvaluation Study
In one paragraph

Article in Nucleic acids research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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  16. Identifying regulatory elements in eukaryotic genomes.Briefings in functional genomics & proteomics · 2009
    Review
  17. Article
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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

2 authors.

Oliver D KingDepartment of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, 250 Longwood Avenue, SGMB-322, Boston, MA 02115, USA.
Frederick P Roth

Funding

Predicting gene attributes from patterns of annotations.F32HG002552 · NHGRI · HARVARD UNIVERSITY (MEDICAL SCHOOL) · PI KING, OLIVER D · 2002 to 2003
$85k
NHGRI NIH HHS F32 HG002552
6 · The paper itself

Abstract

We introduce a non-parametric representation of transcription factor binding sites which can model arbitrary dependencies between positions. As two parameters are varied, this representation smoothly interpolates between the empirical distribution of binding sites and the standard position-specific scoring matrix (PSSM). In a test of generalization to unseen binding sites using 10-fold cross-validation on known binding sites for 95 TRANSFAC transcription factors, this representation outperforms PSSMs on between 65 and 89 of the 95 transcription factors, depending on the choice of the two adjustable parameters. We also discuss how the non- parametric representation may be incorporated into frameworks for finding binding sites given only a collection of unaligned promoter regions.

Indexed as

Models, StatisticalBase SequenceBinding SitesHumansSequence Analysis, DNAStatistics, NonparametricTranscription FactorsTranscription Factors

Identifiers

PMID14500844
PMCPMC206482

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.