Evidence map›Paper›PMID 12824368›Full record

ArticleNucleic acids research2003

SiteSeer: Visualisation and analysis of transcription factor binding sites in nucleotide sequences.

Paul E Boardman, Stephen G Oliver, Simon J Hubbard

Open access · greenAbstract read
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 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.8field-weighted citation impact, top 29% 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

6 citing papers in PubMed, 19 citations in OpenAlex.

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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.

Paul E BoardmanDepartment of Biomolecular Sciences, University of Manchester Institute of Science and Technology, PO Box 88, Manchester M60 1QD, UK.
Stephen G Oliver
Simon J Hubbard
University of Manchester · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The regulation of gene expression is a fundamental process within every living cell, which allows organisms to manage the precise levels of functional gene products with high sensitivity. It is well established that specific DNA sequences located upstream of the transcriptional start site are important in facilitating the binding of regulatory proteins that control the transcription of the gene. Indeed, microarray-based studies have successfully mined the upstream regions of co-expressed genes and discovered over-represented sequences corresponding to known promoter sites. Here we describe a tool for the visualisation of mapped transcription factor binding sites in the upstream regions of either single or grouped eukaryotic genes, which allows users to examine the positions of known and user-defined sites (http://rocky.bms.umist.ac.uk/SiteSeer/). SiteSeer allows the user to map different sections of the TRANSFAC and SCPD databases (or a set of user-defined sites) onto nucleotide sequences. Additionally, users may restrict the analysis by expectation values for certain DNA words as well as by known binding sites specific to a given organism. We believe this tool will prove particularly valuable for biologists who wish to examine sets of co-expressed or functionally-related genes and those who wish to visualise the positions of promoter sequences and generate displays for publications.

Indexed as

Software5' Flanking RegionBase SequenceBinding SitesColorComputer GraphicsDatabases, Nucleic AcidGenes, FungalInternetPromoter Regions, GeneticSaccharomyces cerevisiaeSequence Analysis, DNATranscription FactorsUser-Computer InterfaceTranscription Factors

Identifiers

PMID12824368
PMCPMC168918
OpenAlexW2160917321

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.