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    Discovering approximate-associated sequence patterns for protein-DNA interactions

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    Type
    Article
    Authors
    Chan, Tak Ming
    Wong, Ka Chun
    Lee, Kin Hong
    Wong, Man Hon
    Lau, Chi Kong
    Tsui, Stephen Kwok Wing
    Leung, Kwong Sak
    KAUST Department
    Computer Science Program
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Date
    2010-12-30
    Online Publication Date
    2010-12-30
    Print Publication Date
    2011-02-15
    Permanent link to this record
    http://hdl.handle.net/10754/594175
    
    Metadata
    Show full item record
    Abstract
    Motivation: The bindings between transcription factors (TFs) and transcription factor binding sites (TFBSs) are fundamental protein-DNA interactions in transcriptional regulation. Extensive efforts have been made to better understand the protein-DNA interactions. Recent mining on exact TF-TFBS-associated sequence patterns (rules) has shown great potentials and achieved very promising results. However, exact rules cannot handle variations in real data, resulting in limited informative rules. In this article, we generalize the exact rules to approximate ones for both TFs and TFBSs, which are essential for biological variations. Results: A progressive approach is proposed to address the approximation to alleviate the computational requirements. Firstly, similar TFBSs are grouped from the available TF-TFBS data (TRANSFAC database). Secondly, approximate and highly conserved binding cores are discovered from TF sequences corresponding to each TFBS group. A customized algorithm is developed for the specific objective. We discover the approximate TF-TFBS rules by associating the grouped TFBS consensuses and TF cores. The rules discovered are evaluated by matching (verifying with) the actual protein-DNA binding pairs from Protein Data Bank (PDB) 3D structures. The approximate results exhibit many more verified rules and up to 300% better verification ratios than the exact ones. The customized algorithm achieves over 73% better verification ratios than traditional methods. Approximate rules (64-79%) are shown statistically significant. Detailed variation analysis and conservation verification on NCBI records demonstrate that the approximate rules reveal both the flexible and specific protein-DNA interactions accurately. The approximate TF-TFBS rules discovered show great generalized capability of exploring more informative binding rules. © The Author 2010. Published by Oxford University Press. All rights reserved.
    Citation
    Chan T-M, Wong K-C, Lee K-H, Wong M-H, Lau C-K, et al. (2010) Discovering approximate-associated sequence patterns for protein-DNA interactions. Bioinformatics 27: 471–478. Available: http://dx.doi.org/10.1093/bioinformatics/btq682.
    Sponsors
    The research is supported by the grant CUHK414708 from the Research Grants Council of the Hong Kong SAR, China, and Focused Investment Scheme D on Hong Kong Bioinformatics Centre (Project Number: 1904014) from The Chinese University of Hong Kong.
    Publisher
    Oxford University Press (OUP)
    Journal
    Bioinformatics
    DOI
    10.1093/bioinformatics/btq682
    PubMed ID
    21193520
    ae974a485f413a2113503eed53cd6c53
    10.1093/bioinformatics/btq682
    Scopus Count
    Collections
    Articles; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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