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Graphic Network based Methods in Discovering TFBS Motifs

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2012, Master of Science, Ohio State University, Biophysics.
To find motifs of transcriptional factors binding sites (TFBS) is essential to understand many biological processes in a cell. Currently the algorithms in discovering the motifs can be divided into three categories: word numeration methods, probabilistic based methods and newly developed graphic network based methods. Graphic network based methods show their advantages over the other two categories of algorithms on prediction accuracy, sensitivity and specificity. This thesis gives a comprehensive overview the main motif discovery methods which are being used now and especially, focuses on the introduction of graphic network based methods. In addition, a study in discovering the TFBS motifs of E2F1, which is a well-known transcription factor, is performed by applying graphic network based algorithms.
Kun Huang (Advisor)
Victor Jin (Committee Member)
38 p.

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Citations

  • Li, L. (2012). Graphic Network based Methods in Discovering TFBS Motifs [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1325276730

    APA Style (7th edition)

  • Li, Lizhi. Graphic Network based Methods in Discovering TFBS Motifs. 2012. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1325276730.

    MLA Style (8th edition)

  • Li, Lizhi. "Graphic Network based Methods in Discovering TFBS Motifs." Master's thesis, Ohio State University, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=osu1325276730

    Chicago Manual of Style (17th edition)