IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0054843.html
   My bibliography  Save this article

A Composite Method Based on Formal Grammar and DNA Structural Features in Detecting Human Polymerase II Promoter Region

Author

Listed:
  • Sutapa Datta
  • Subhasis Mukhopadhyay

Abstract

An important step in understanding gene regulation is to identify the promoter regions where the transcription factor binding takes place. Predicting a promoter region de novo has been a theoretical goal for many researchers for a long time. There exists a number of in silico methods to predict the promoter region de novo but most of these methods are still suffering from various shortcomings, a major one being the selection of appropriate features of promoter region distinguishing them from non-promoters. In this communication, we have proposed a new composite method that predicts promoter sequences based on the interrelationship between structural profiles of DNA and primary sequence elements of the promoter regions. We have shown that a Context Free Grammar (CFG) can formalize the relationships between different primary sequence features and by utilizing the CFG, we demonstrate that an efficient parser can be constructed for extracting these relationships from DNA sequences to distinguish the true promoter sequences from non-promoter sequences. Along with CFG, we have extracted the structural features of the promoter region to improve upon the efficiency of our prediction system. Extensive experiments performed on different datasets reveals that our method is effective in predicting promoter sequences on a genome-wide scale and performs satisfactorily as compared to other promoter prediction techniques.

Suggested Citation

  • Sutapa Datta & Subhasis Mukhopadhyay, 2013. "A Composite Method Based on Formal Grammar and DNA Structural Features in Detecting Human Polymerase II Promoter Region," PLOS ONE, Public Library of Science, vol. 8(2), pages 1-11, February.
  • Handle: RePEc:plo:pone00:0054843
    DOI: 10.1371/journal.pone.0054843
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0054843
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0054843&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0054843?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Christopher Loose & Kyle Jensen & Isidore Rigoutsos & Gregory Stephanopoulos, 2006. "A linguistic model for the rational design of antimicrobial peptides," Nature, Nature, vol. 443(7113), pages 867-869, October.
    2. Vladimir B Bajic & Sin Lam Tan & Alan Christoffels & Christian Schönbach & Leonard Lipovich & Liang Yang & Oliver Hofmann & Adele Kruger & Winston Hide & Chikatoshi Kai & Jun Kawai & David A Hume & Pi, 2006. "Mice and Men: Their Promoter Properties," PLOS Genetics, Public Library of Science, vol. 2(4), pages 1-13, April.
    3. David B. Searls, 2002. "The language of genes," Nature, Nature, vol. 420(6912), pages 211-217, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sutapa Datta & Subhasis Mukhopadhyay, 2015. "A Grammar Inference Approach for Predicting Kinase Specific Phosphorylation Sites," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-19, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sutapa Datta & Subhasis Mukhopadhyay, 2015. "A Grammar Inference Approach for Predicting Kinase Specific Phosphorylation Sites," PLOS ONE, Public Library of Science, vol. 10(4), pages 1-19, April.
    2. Moghaddasi, Hanieh & Rezaei, Soghra & Darooneh, Amir Hossein & Heshmati, Emran & Khalifeh, Khosrow, 2020. "A comparative analysis of dipeptides distribution in eukaryotes and prokaryotes by statistical mechanics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    3. Xiaobei Zhao & Eivind Valen & Brian J Parker & Albin Sandelin, 2011. "Systematic Clustering of Transcription Start Site Landscapes," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-16, August.
    4. William F Porto & Állan S Pires & Octavio L Franco, 2012. "CS-AMPPred: An Updated SVM Model for Antimicrobial Activity Prediction in Cysteine-Stabilized Peptides," PLOS ONE, Public Library of Science, vol. 7(12), pages 1-7, December.
    5. Deepesh Nagarajan & Tushar Nagarajan & Neha Nanajkar & Nagasuma Chandra, 2019. "A Uniform In Vitro Efficacy Dataset to Guide Antimicrobial Peptide Design," Data, MDPI, vol. 4(1), pages 1-13, February.
    6. Ben Jacob, Eshel & Shapira, Yoash & Tauber, Alfred I., 2006. "Seeking the foundations of cognition in bacteria: From Schrödinger's negative entropy to latent information," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 359(C), pages 495-524.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0054843. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.