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Mining Gene Regulatory Motifs Using the Concept of Sequence Coverage

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2014, Master of Science (MS), Ohio University, Computer Science (Engineering and Technology).
Transcription factors bind to specific sequence elements present in the promoter regions of co-expressed genes and regulate their expression. Genes expressed in an identical manner may have the same transcription factors binding to them, the binding sites being similar with a probable difference of one or two nucleotides. Therefore, a direct inference is that similar sequence elements are present in all the co-expressed genes, with a moderate to high occurrence frequency. These elements are termed motifs. The bioinformatics society currently has a number of effective de-novo motif discovery tools that endeavor to find these motifs through a search for over-represented patterns in gene promoter sequences. Any significant binding sites found through the search procedure will help understand the mechanisms of gene regulation. One significant drawback of current tools is the volume of candidate motifs reported, often numbering in the hundreds or greater, which may result in impractical lab verification in terms of time and resources. This paper presents three methods for solving the problem, namely Random Method, Greedy Method and Hill climbing Method, which substantially reduce the list of candidate motifs to those showing greatest potential.
Lonnie Welch, Dr. (Advisor)
84 p.

Recommended Citations

Citations

  • Naik, A. (2014). Mining Gene Regulatory Motifs Using the Concept of Sequence Coverage [Master's thesis, Ohio University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1408699463

    APA Style (7th edition)

  • Naik, Ashwini. Mining Gene Regulatory Motifs Using the Concept of Sequence Coverage. 2014. Ohio University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1408699463.

    MLA Style (8th edition)

  • Naik, Ashwini. "Mining Gene Regulatory Motifs Using the Concept of Sequence Coverage." Master's thesis, Ohio University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1408699463

    Chicago Manual of Style (17th edition)