Target Explorer: an automated tool for the identification of new target genes for a specified set of transcription factors

Sosinsky, Alona; Bonin, Christopher; Mann, Richard S.; Honig, Barry

doi:10.1093/nar/gkg544

Cited by 85 publications

(98 citation statements)

References 14 publications

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“…This method became increasingly efficient as various aspects of enhancer organization were revealed. Other utilities included Auilix Biopharma's GENEGROKKER software for mixed probabilistic models involving regular expressions͞position-weighted matrices͞consensus sequences for the fly genome, F LYENHANCER (www.flyenhancer.org) for Boolean models with simple consensus sequences for the fly and mosquito genomes (courtesy of www.opengenomics.org), and Target Explorer (http:͞͞trantor.bioc.columbia.edu͞Target Explorer) for searches based on position-weighted matrices of fly and mosquito (10). Analysis for shared motifs and sequence comparison for Fig.…”

Section: Methodsmentioning

confidence: 99%

Coordinate enhancers share common organizational features in the Drosophila genome

Erives

Levine

2004

Proc. Natl. Acad. Sci. U.S.A.

121

130

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The evolution of animal diversity depends on changes in the regulation of a relatively fixed set of protein-coding genes. To understand how these changes might arise, we examined the organization of shared sequence motifs in four coordinately regulated neurogenic enhancers that direct similar patterns of gene expression in the early Drosophila embryo. All four enhancers possess similar arrangements of a subset of putative regulatory elements. These shared features were used to identify a neurogenic enhancer in the distantly related Anopheles genome. We suggest that the constrained organization of metazoan enhancers may be essential for their ability to produce precise patterns of gene expression during development. Organized binding sites should facilitate the identification of regulatory codes that link primary DNA sequence information with predicted patterns of gene activity.

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Section: Methodsmentioning

confidence: 99%

Coordinate enhancers share common organizational features in the Drosophila genome

Erives

Levine

2004

Proc. Natl. Acad. Sci. U.S.A.

121

130

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show abstract

“…We identified clusters of putative TCF binding sites in the intergenic and intronic regions of nkd and CG6234 using an online tool called Target Explorer (http://trantor.bioc.columbia.edu/Target_Explorer; Sosinsky et al, 2003). The matrix that defined the search criteria is based on the DNA-binding data from the sloppy pair1, evenskipped, Ultrabithorax and decapentapleigic Wg-dependent enhancers (Riese et al, 1997;Lee and Frasch, 2000;Yang et al, 2000;Knirr and Frasch, 2001).…”

Section: Ctbp Binding To Wres In Endogenous Wg Transcriptional Targetsmentioning

confidence: 99%

C-terminal-binding protein directly activates and represses Wnt transcriptional targets in Drosophila

Fang¹,

Li²,

Blauwkamp³

et al. 2006

EMBO J

155

238

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Regulation of Wnt transcriptional targets is thought to occur by a transcriptional switch. In the absence of Wnt signaling, sequence‐specific DNA‐binding proteins of the TCF family repress Wnt target genes. Upon Wnt stimulation, stabilized β‐catenin binds to TCFs, converting them into transcriptional activators. C‐terminal‐binding protein (CtBP) is a transcriptional corepressor that has been reported to inhibit Wnt signaling by binding to TCFs or by preventing β‐catenin from binding to TCF. Here, we show that CtBP is also required for the activation of some Wnt targets in Drosophila. CtBP is recruited to Wnt‐regulated enhancers in a Wnt‐dependent manner, where it augments Armadillo (the fly β‐catenin) transcriptional activation. We also found that CtBP is required for repression of a subset of Wnt targets in the absence of Wnt stimulation, but in a manner distinct from previously reported mechanisms. CtBP binds to Wnt‐regulated enhancers in a TCF‐independent manner and represses target genes in parallel with TCF. Our data indicate dual roles for CtBP as a gene‐specific activator and repressor of Wnt target gene transcription.

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“…The method combines a search algorithm for individual TFBS and a distance correlation function. TargetExplorer applies a similar approach to find promoter modules in DNA sequences as described by Sosinsky et al [132]. More sophisticated methods were developed by Alkema et al [133,134] and Frith et al [135] supporting the validity of detected modules with statistical scores.…”

Section: Promoter Modules and Screening For Co-regulationmentioning

confidence: 99%

Transforming omics data into context: Bioinformatics on genomics and proteomics raw data

et al. 2006

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Differential gene expression analysis and proteomics have exerted significant impact on the elucidation of concerted cellular processes, as simultaneous measurement of hundreds to thousands of individual objects on the level of RNA and protein ensembles became technically feasible. The availability of such data sets has promised a profound understanding of phenomena on an aggregate level, expressed as the phenotypic response (observables) of cells, e.g., in the presence of drugs, or characterization of cells and tissue displaying distinct patho-physiological states. However, the step of transforming these data into context, i.e., linking distinct expression or abundance patterns with phenotypic observables -and furthermore enabling a sound biological interpretation on the level of reaction networks and concerted pathways, is still a major shortcoming. This finding is certainly based on the enormous complexity embedded in cellular reaction networks, but a variety of computational approaches have been developed over the last few years to overcome these issues. This review provides an overview on computational procedures for analysis of genomic and proteomic data introducing a sequential analysis workflow: Explorative statistics for deriving a first, from the purely statistical viewpoint, relevant candidate gene/protein list, followed by co-regulation and network analysis to biologically expand this core list toward functional networks and pathways. The review on these procedures is complemented by example applications tailored at identification of disease-associated proteins. Optimization of computational procedures involved, in conjunction with the continuous increase in additional biological data, clearly has the potential of boosting our understanding of processes on a cell-wide level.

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Target Explorer: an automated tool for the identification of new target genes for a specified set of transcription factors

Cited by 85 publications

References 14 publications

Coordinate enhancers share common organizational features in the Drosophila genome

Coordinate enhancers share common organizational features in the Drosophila genome

C-terminal-binding protein directly activates and represses Wnt transcriptional targets in Drosophila

Transforming omics data into context: Bioinformatics on genomics and proteomics raw data

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