DocumentCode
2289913
Title
RNA secondary structure prediction algorithm based on combinatorial optimization algorithm and SVMs method
Author
He Jing-yuan ; Mu Chao ; Huang Hai-hun
Author_Institution
Coll. of Comput. Sci., Chongqing Univ., Chongqing, China
fYear
2012
fDate
6-8 July 2012
Firstpage
715
Lastpage
719
Abstract
A new RNA secondary structure prediction algorithm that can predict pseudoknots is proposed, it combines the stem-loop combinatorial optimization algorithm and SVMs(Support Vector Machines, SVMs) method. The algorithm firstly finds out the optimal stem-loop structure and suboptimum structures based on dynamic neighbor topology particle swarm optimization algorithm, and then puts these loops into SVMs. The output from SVMs can decide whether there exist a pseudoknot. The experimental results demonstrate the superiority of our algorithm over the other methods in terms of solution quality and convergence rates.
Keywords
RNA; biology computing; cellular biophysics; particle swarm optimisation; support vector machines; RNA secondary structure prediction; SVM method; convergence rates; dynamic neighbor topology particle swarm optimization; optimal stem-loop structure; pseudoknots; solution quality; stem-loop combinatorial optimization; suboptimum structures; support vector machines; Classification algorithms; Convergence; Heuristic algorithms; Optimization; Prediction algorithms; RNA; Topology; RNA secondary structure prediction; SVMs; dynamic neighbor topology; particle optimization algorithm;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Control and Automation (WCICA), 2012 10th World Congress on
Conference_Location
Beijing
Print_ISBN
978-1-4673-1397-1
Type
conf
DOI
10.1109/WCICA.2012.6357971
Filename
6357971
Link To Document