Paper Info
Title
Population-based Modified Extremal Optimization for Contact Map Overlap Maximization Problem
Abstract
The three-dimensional structures of proteins provide biogenic functions for biological activities. Proteins that have similar three-dimensional structures usually have similar biological functions. Therefore, many researchers focus on the techniques for comparing the three-dimensional structures of proteins. Many of these techniques for comparing protein structures are based on protein structure alignment, which is one of the most effective methods for extracting similar strutures. The Contact Map Overlap (CMO) maximization problem (for short, the CMO problem) is formulated as a combinatorial optimization for finding the optimal structure alignments. In this paper, we propose a novel bio-inspired heuristic using Population-based Modified Extremal Optimization (PMEO) for the CMO problem. The proposed heuristic has two features. First, the proposed heuristic uses PMEO. There are multiple individuals in a population which repeat alternation of generations. Second, to improve the search efficiency, individuals copy a sub-structure of an individual with good sub-structures at each alternation of generations.
Year
DOI
Venue
2013
10.1109/IIAI-AAI.2013.61
Advanced Applied Informatics
Keywords
Field
DocType
optimal structure alignment,maximization problem,population-based modified extremal optimization,similar three-dimensional structure,protein structure,similar strutures,biological activity,proposed heuristic,cmo problem,similar biological function,contact map overlap maximization,three-dimensional structure,proteins
Population,Heuristic,Mathematical optimization,Extremal optimization,Combinatorial mathematics,Computer science,Combinatorial optimization,Optimization problem,Maximization
Conference
ISBN
Citations 
PageRank 
978-1-4799-2134-8
2
0.37
References 
Authors
15
4
Name
Order
Citations
PageRank
Akihiro Nakada120.37
Keiichi Tamura23713.86
H. Kitakami39449.68
Yoshifumi Takahashi421.39