By Topic

Non-Isomorphic Coding in Lattice Model and its Impact for Protein Folding Prediction Using Genetic Algorithm

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Hoque, M.T. ; Gippsland Sch. of Inf. Technol., Monash Univ., Clayton, Vic. ; Chetty, M. ; Dooley, L.S.

Traditional encodings for hydrophobic(H)-hydrophilic(P) model or HP lattice models is isomorphic, which adds unwanted variations for the same solution, thereby slowing convergence. In this paper a novel non-isomorphic encoding scheme is presented for HP lattice model, which constrains the search space. In addition, similarity comparisons are made easier and more consistent and it will be shown that non-deterministic search approach such as genetic algorithm (GA) converges faster when non-isomorphic encoding is employed

Published in:

Computational Intelligence and Bioinformatics and Computational Biology, 2006. CIBCB '06. 2006 IEEE Symposium on

Date of Conference:

28-29 Sept. 2006