Paper Info
Title
Heuristic Strategy for Geometric Hashing Based Protein Structure Comparison of Ellipsoidal Representation
Abstract
Many protein structure comparison methods use secondary structure information to do fast structure similarity search for initial alignment finding and refine the results from possible optimal candidate solutions by iteratively dynamic programming to optimize the final results. In this paper, we develop a method, Ellipsoidal Model Protein Structure Comparison, based on the concept of secondary structure elements alignment followed by iteratively refinement. In order to utilize all possible structure information to obtain alternative solutions for further analysis, we use ellipsoidal model to represent not only mainly -helices and -sheets, but the remaining fragments for structural alignment. Different heuristic filters and geometric hashing based global alignment estimation are applied for quick finding better initial alignments. We also provide top-N solutions without increasing extra computational time rather than only best solution in the previous works. Now, we provide the online web service, Ballerina (http://ballerina.csie.ntu.edu.tw/), for protein structure comparison.
Year
DOI
Venue
2007
10.1109/BIBM.2007.37
BIBM
Keywords
Field
DocType
structural similarity,hidden markov models,clustering algorithms,biomedical engineering,solid modeling,dynamic programming,web service,bioinformatics,protein engineering,secondary structure,filtering,structure alignment
Dynamic programming,Structural alignment,Heuristic,Computer science,Filter (signal processing),Solid modeling,Artificial intelligence,Geometric hashing,Bioinformatics,Cluster analysis,Nearest neighbor search,Machine learning
Conference
ISSN
ISBN
Citations 
2156-1125
0-7695-3031-1
0
PageRank 
References 
Authors
0.34
14
4
Name
Order
Citations
PageRank
Yhi Shiau111.41
Jia-Nan Wang200.34
Yu-Feng Huang300.34
Chien-Kang Huang415011.52