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    Comparison of Transcription Factor Binding Site Models

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    Shariful Bhuyan Thesis.pdf
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    Type
    Thesis
    Authors
    Bhuyan, Sharifulislam
    Advisors
    Bajic, Vladimir B. cc
    Committee members
    Gao, Xin cc
    Zhang, Xiangliang cc
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2012-05
    Permanent link to this record
    http://hdl.handle.net/10754/244613
    
    Metadata
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    Abstract
    Modeling of transcription factor binding sites (TFBSs) and TFBS prediction on genomic sequences are important steps to elucidate transcription regulatory mechanism. Dependency of transcription regulation on a great number of factors such as chemical specificity, molecular structure, genomic and epigenetic characteristics, long distance interaction, makes this a challenging problem. Different experimental procedures generate evidence that DNA-binding domains of transcription factors show considerable DNA sequence specificity. Probabilistic modeling of TFBSs has been moderately successful in identifying patterns from a family of sequences. In this study, we compare performances of different probabilistic models and try to estimate their efficacy over experimental TFBSs data. We build a pipeline to calculate sensitivity and specificity from aligned TFBS sequences for several probabilistic models, such as Markov chains, hidden Markov models, Bayesian networks. Our work, containing relevant statistics and evaluation for the models, can help researchers to choose the most appropriate model for the problem at hand.
    Citation
    Bhuyan, S. (2012). Comparison of Transcription Factor Binding Site Models. KAUST Research Repository. https://doi.org/10.25781/KAUST-SM4HU
    DOI
    10.25781/KAUST-SM4HU
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-SM4HU
    Scopus Count
    Collections
    MS Theses; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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