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  • Genetic Algorithm in Ab Initio Protein Structure Prediction Using Low Resolution Model: A Review

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    Author(s)
    Hoque, Md Tamjidul
    Chetty, Madhu
    Sattar, Abdul
    Griffith University Author(s)
    Sattar, Abdul
    Year published
    2009
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    Abstract
    Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded three-dimensional (3D) shape. This specific folded shape enables proteins to perform specific tasks. The protein structure prediction (PSP) by ab initio or de novo approach is promising amongst various available computational methods and can help to unravel the important relationship between sequence and its corresponding structure. This article presents the ab initio protein structure prediction as a conformational search problem in low resolution model using genetic algorithm. As a review, the essence of twin removal, ...
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    Proteins are sequences of amino acids bound into a linear chain that adopt a specific folded three-dimensional (3D) shape. This specific folded shape enables proteins to perform specific tasks. The protein structure prediction (PSP) by ab initio or de novo approach is promising amongst various available computational methods and can help to unravel the important relationship between sequence and its corresponding structure. This article presents the ab initio protein structure prediction as a conformational search problem in low resolution model using genetic algorithm. As a review, the essence of twin removal, intelligence in coding, the development and application of domain specific heuristics garnered from the properties of the resulting model and the protein core formation concept discussed are all highly relevant in attempting to secure the best solution.
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    Book Title
    Biomedical Data and Applications
    Volume
    224
    DOI
    https://doi.org/10.1007/978-3-642-02193-0_14
    Copyright Statement
    © 2009 Springer. The attached file is reproduced here in accordance with the copyright policy of the publisher. The original publication is available at www.springerlink.com
    Subject
    Biological mathematics
    Other information and computing sciences not elsewhere classified
    Publication URI
    http://hdl.handle.net/10072/26547
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    • Book chapters

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