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Developing the Cis-Regulatory Association Model (CRAM) to Identify Combinations of Transcription Factors in ChIP-Seq Data

Kennedy, Brian Alexander

Abstract Details

2010, Master of Science, Ohio State University, Computer Science and Engineering.
There are approximately 2,600 human transcription factors which may cis-regulate the expression of proximal genes. These TFs may further interact with one another and exhibit different behavior in combination than individually, cis-regulatory modules (CRM). Even simple 2 and 3 TF combinations could form over 2.9 billion different cis-regulatory modules. Testing the functionality of these modules experimentally will be a massive undertaking. CRAM, the Cis-Regulatory Association Modeler predicts functional regulatory modules in silico using TFs found in sequences searched for TF motifs defined by Position Weight Matrices. This technique targets ChIP-seq data and finds CRMs which are over-represented in the target sequences compared to a random background, or another contrasting sample of sequences, by using contrast frequent item-set mining in the experimental ChIP-seq peaks and the control sample. The error with which these CRMs may be separated from the random background by a variety of features is used to determine which CRMs are truly specific to the experimental ChIP-seq sample under degree of motif matching, relative position, and genetic conservation. Feed-forward neural networks are used to learn the function which specifies the classifiability of each CRM and calculate the error with which they are compared. Several other programs use a comparable approach; however, the application of neural networks specifically and contrast item-set mining is novel.
Victor Jin, PhD (Advisor)
Machiraju Raghu, PhD (Committee Chair)
56 p.

Recommended Citations

Citations

  • Kennedy, B. A. (2010). Developing the Cis-Regulatory Association Model (CRAM) to Identify Combinations of Transcription Factors in ChIP-Seq Data [Master's thesis, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1291138540

    APA Style (7th edition)

  • Kennedy, Brian. Developing the Cis-Regulatory Association Model (CRAM) to Identify Combinations of Transcription Factors in ChIP-Seq Data. 2010. Ohio State University, Master's thesis. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1291138540.

    MLA Style (8th edition)

  • Kennedy, Brian. "Developing the Cis-Regulatory Association Model (CRAM) to Identify Combinations of Transcription Factors in ChIP-Seq Data." Master's thesis, Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1291138540

    Chicago Manual of Style (17th edition)