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Efficient Computation of Fitness Function by Pruning in Hydrophobic-Hydrophilic Model

Houqe, Tamjid; Chetty, Madhu and Dooley, Laurence S. (2005). Efficient Computation of Fitness Function by Pruning in Hydrophobic-Hydrophilic Model. In: ed. Biological and Medical Data Analysis. Lecture Notes in Computer Science, 3745. Berlin: Springer-Verlag, pp. 346–354.

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The use of Genetic Algorithms in a 2D Hydrophobic-Hydrophilic (HP) model in protein folding prediction application requires frequent fitness function computations. While the fitness computation is linear, the overhead incurred is significant with respect to the protein folding prediction problem. Any reduction in the computational cost will therefore assist in more efficiently searching the enormous solution space for protein folding prediction. This paper proposes a novel pruning strategy that exploits the inherent properties of the HP model and guarantee reduction of the computational complexity during an ordered traversal of the amino acid chain sequences for fitness computation, truncating the sequence by at least one residue.

Item Type: Book Chapter
ISBN: 3-540-29674-3, 978-3-540-29674-4
Academic Unit/Department: Mathematics, Computing and Technology > Computing & Communications
Interdisciplinary Research Centre: Centre for Research in Computing (CRC)
Item ID: 10554
Depositing User: Laurence Dooley
Date Deposited: 10 Apr 2008
Last Modified: 02 Dec 2010 20:07
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