Evidence map›Paper›PMID 16756683›Full record

ArticleBMC bioinformatics2006

BLISS: binding site level identification of shared signal-modules in DNA regulatory sequences.

Hailong Meng, Arunava Banerjee, Lei Zhou

Abstract readComparative Study
In one paragraph

Article in BMC bioinformatics, 2006. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

1 citing paper in PubMed.

  1. Article
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.

Hailong MengDepartment of Molecular Genetics and Microbiology, UF Shands Cancer Center, College of Medicine, University of Florida, Gainesville, FL 32610, USA. hmeng@cise.ufl.edu
Arunava Banerjee
Lei Zhou

Funding

Probing Complexity of UV Induced Apoptosis in DrosophilaR01CA095542 · NCI · UNIVERSITY OF FLORIDA · PI ZHOU, LEI · 2003 to 2007
$1.2M
NCI NIH HHS CA095542NCI NIH HHS R01 CA095542
6 · The paper itself

Abstract

backgroundRegulatory modules are segments of the DNA that control particular aspects of gene expression. Their identification is therefore of great importance to the field of molecular genetics. Each module is composed of a distinct set of binding sites for specific transcription factors. Since experimental identification of regulatory modules is an arduous process, accurate computational techniques that supplement this process can be very beneficial. Functional modules are under selective pressure to be evolutionarily conserved. Most current approaches therefore attempt to detect conserved regulatory modules through similarity comparisons at the DNA sequence level. However, some regulatory modules, despite the conservation of their responsible binding sites, are embedded in sequences that have little overall similarity.

resultsIn this study, we present a novel approach that detects conserved regulatory modules via comparisons at the binding site level. The technique compares the binding site profiles of orthologs and identifies those segments that have similar (not necessarily identical) profiles. The similarity measure is based on the inner product of transformed profiles, which takes into consideration the p values of binding sites as well as the potential shift of binding site positions. We tested this approach on simulated sequence pairs as well as real world examples. In both cases our technique was able to identify regulatory modules which could not to be identified using sequence-similarity based approaches such as rVista 2.0 and Blast.

conclusionThe results of our experiments demonstrate that, for sequences with little overall similarity at the DNA sequence level, it is still possible to identify conserved regulatory modules based solely on binding site profiles.

Indexed as

AnimalsBase SequenceBinding SitesComputer SimulationConserved SequenceDatabases, GeneticDNADrosophila melanogasterEvolution, MolecularInternetModels, GeneticNormal DistributionRegulatory Sequences, Nucleic AcidSequence AlignmentSequence Analysis, DNATranscription FactorsDNATranscription Factors

Identifiers

PMID16756683
PMCPMC1526457

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LicenceCC BY
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Registered trials

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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.