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Generic eukaryotic core promoter prediction using structural features of DNA

Thomas Abeel (UGent) , Yvan Saeys (UGent) , Eric Bonnet (UGent) , Pierre Rouzé (UGent) and Yves Van de Peer (UGent)
(2008) GENOME RESEARCH. 18(2). p.310-323
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Abstract
Despite many recent efforts, in silico identification of promoter regions is still in its infancy. However, the accurate identification and delineation of promoter regions is important for several reasons, such as improving genome annotation and devising experiments to study and understand transcriptional regulation. Current methods to identify the core region of promoters require large amounts of high-quality training data and often behave like black box models that output predictions that are difficult to interpret. Here, we present a novel approach for predicting promoters in whole-genome sequences by using large-scale structural properties of DNA. Our technique requires no training, is applicable to many eukaryotic genomes, and performs extremely well in comparison with the best available promoter prediction programs. Moreover, it is fast, simple in design, and has no size constraints, and the results are easily interpretable. We compared our approach with 14 current state-of-the-art implementations using human gene and transcription start site data and analyzed the ENCODE region in more detail. We also validated our method on 12 additional eukaryotic genomes, including vertebrates, invertebrates, plants, fungi, and protists.
Keywords
POLYMERASE-II PROMOTERS, TRANSCRIPTION START SITES, TATA-BINDING PROTEIN, DISTINCTIVE MECHANICAL PROPERTY, GENOME-WIDE ANALYSIS, CPG ISLANDS, DROSOPHILA-MELANOGASTER, COMPREHENSIVE ANALYSIS, FLANKING SEQUENCES, PLANT GENOMES

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MLA
Abeel, Thomas, et al. “Generic Eukaryotic Core Promoter Prediction Using Structural Features of DNA.” GENOME RESEARCH, vol. 18, no. 2, 2008, pp. 310–23, doi:10.1101/gr.6991408.
APA
Abeel, T., Saeys, Y., Bonnet, E., Rouzé, P., & Van de Peer, Y. (2008). Generic eukaryotic core promoter prediction using structural features of DNA. GENOME RESEARCH, 18(2), 310–323. https://doi.org/10.1101/gr.6991408
Chicago author-date
Abeel, Thomas, Yvan Saeys, Eric Bonnet, Pierre Rouzé, and Yves Van de Peer. 2008. “Generic Eukaryotic Core Promoter Prediction Using Structural Features of DNA.” GENOME RESEARCH 18 (2): 310–23. https://doi.org/10.1101/gr.6991408.
Chicago author-date (all authors)
Abeel, Thomas, Yvan Saeys, Eric Bonnet, Pierre Rouzé, and Yves Van de Peer. 2008. “Generic Eukaryotic Core Promoter Prediction Using Structural Features of DNA.” GENOME RESEARCH 18 (2): 310–323. doi:10.1101/gr.6991408.
Vancouver
1.
Abeel T, Saeys Y, Bonnet E, Rouzé P, Van de Peer Y. Generic eukaryotic core promoter prediction using structural features of DNA. GENOME RESEARCH. 2008;18(2):310–23.
IEEE
[1]
T. Abeel, Y. Saeys, E. Bonnet, P. Rouzé, and Y. Van de Peer, “Generic eukaryotic core promoter prediction using structural features of DNA,” GENOME RESEARCH, vol. 18, no. 2, pp. 310–323, 2008.
@article{417320,
  abstract     = {{Despite many recent efforts, in silico identification of promoter regions is still in its infancy. However, the accurate identification and delineation of promoter regions is important for several reasons, such as improving genome annotation and devising experiments to study and understand transcriptional regulation. Current methods to identify the core region of promoters require large amounts of high-quality training data and often behave like black box models that output predictions that are difficult to interpret. Here, we present a novel approach for predicting promoters in whole-genome sequences by using large-scale structural properties of DNA. Our technique requires no training, is applicable to many eukaryotic genomes, and performs extremely well in comparison with the best available promoter prediction programs. Moreover, it is fast, simple in design, and has no size constraints, and the results are easily interpretable. We compared our approach with 14 current state-of-the-art implementations using human gene and transcription start site data and analyzed the ENCODE region in more detail. We also validated our method on 12 additional eukaryotic genomes, including vertebrates, invertebrates, plants, fungi, and protists.}},
  author       = {{Abeel, Thomas and Saeys, Yvan and Bonnet, Eric and Rouzé, Pierre and Van de Peer, Yves}},
  issn         = {{1088-9051}},
  journal      = {{GENOME RESEARCH}},
  keywords     = {{POLYMERASE-II PROMOTERS,TRANSCRIPTION START SITES,TATA-BINDING PROTEIN,DISTINCTIVE MECHANICAL PROPERTY,GENOME-WIDE ANALYSIS,CPG ISLANDS,DROSOPHILA-MELANOGASTER,COMPREHENSIVE ANALYSIS,FLANKING SEQUENCES,PLANT GENOMES}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{310--323}},
  title        = {{Generic eukaryotic core promoter prediction using structural features of DNA}},
  url          = {{http://doi.org/10.1101/gr.6991408}},
  volume       = {{18}},
  year         = {{2008}},
}

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