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  • Fast computation of the fitness function for protein folding prediction in a 2D hydrophilic-hydrophobic model

    Author(s)
    Tamjidul Hoque, M.
    Chetty, Madhu
    S. Dooley, Laurence
    Griffith University Author(s)
    Hoque, Md T.
    Year published
    2005
    Metadata
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    Abstract
    Protein Folding Prediction (PFP) is essentially an energy minimization problem formalised by the definition of a fitness function. Several PFP models have been proposed including the Hydrophobic-Hydrophilic (HP) model, which is widely used as a test-bed for evaluating new algorithms. The calculation of the fitness is the major computational task in determining the native conformation of a protein in the HP model and this paper presents a new efficient search algorithm (ESA) for deriving the fitness value requiring only O(n) complexity in contrast to the full search approach, which takes O(n2). The improved efficiency of ESA ...
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    Protein Folding Prediction (PFP) is essentially an energy minimization problem formalised by the definition of a fitness function. Several PFP models have been proposed including the Hydrophobic-Hydrophilic (HP) model, which is widely used as a test-bed for evaluating new algorithms. The calculation of the fitness is the major computational task in determining the native conformation of a protein in the HP model and this paper presents a new efficient search algorithm (ESA) for deriving the fitness value requiring only O(n) complexity in contrast to the full search approach, which takes O(n2). The improved efficiency of ESA is achieved by exploiting some intrinsic properties of the HP model, with a resulting reduction of more than 50% in the overall time complexity when compared with the previously reported Caching Approach, with the added benefit that the additional space complexity is linear instead of quadratic.
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    Journal Title
    International Journal of Simulation. Systems, Science and Technology
    Volume
    6
    Issue
    10/11
    Publisher URI
    http://ducati.doc.ntu.ac.uk/uksim/journal.htm
    Subject
    Multi-Disciplinary
    Publication URI
    http://hdl.handle.net/10072/33449
    Collection
    • Journal articles

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