Please use this identifier to cite or link to this item: https://doi.org/10.1504/IJDMB.2007.012966
Title: A Merge-Decoupling Dead End Elimination algorithm for protein side-chain conformation
Authors: Chong, K.F.
Leong, H.W. 
Keywords: Bioinformatics
Data mining
Dead end elimination
DEE
Merge-decoupling algorithm
Protein side-chain conformation prediction
SCCP
Issue Date: 2007
Source: Chong, K.F.,Leong, H.W. (2007). A Merge-Decoupling Dead End Elimination algorithm for protein side-chain conformation. International Journal of Data Mining and Bioinformatics 1 (4) : 372-388. ScholarBank@NUS Repository. https://doi.org/10.1504/IJDMB.2007.012966
Abstract: Dead End Elimination (DEE) is a technique for eliminating rotamers that can not exist in any global minimum energy configuration for the protein side chain conformation problem. A popular method is Simple Goldstein DEE (SG-DEE) which is fast and eliminates rotamers by considering single residues for possible elimination. We present a Merge-Decoupling DEE (MD-DEE) that further reduces the number of rotamers after SG-DEE. MD-DEE works by forming residue-pairs but is fast and, like SG-DEE, is practical even for large proteins. Our experiments show that MD-DEE achieves further reduction in residue elimination (up to 25%) after SG-DEE. Copyright © 2007 Inderscience Enterprises Ltd.
Source Title: International Journal of Data Mining and Bioinformatics
URI: http://scholarbank.nus.edu.sg/handle/10635/39527
ISSN: 17485673
DOI: 10.1504/IJDMB.2007.012966
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