SARNA-Predict: A Simulated Annealing algorithm for RNA secondary structure prediction

被引：0

作者：

Tsang, Herbert H. ^{[1
]}

Wiese, Kay C. ^{[1
]}

机构：

[1] Simon Fraser Univ, Sch Comp Sci, Bioinformat Res Lab, Surrey, BC V3T 2W1, Canada

来源：

PROCEEDINGS OF THE 2006 IEEE SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY | 2006年

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

暂无

中图分类号：

Q [生物科学];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

Ribonucleic Acid (RNA) plays fundamental roles in cellular processes and its structure is directly related to its functions. This paper describes and presents a novel algorithm for RNA secondary structure prediction based on Simulated Annealing (SA). SA is known to be effective in solving many different types of minimization problems and for finding the global minima in the solution space. Based on free energy minimization techniques, this permutation-based SA algorithm heuristically searches for the structure with a free energy value close to the minimum free energy Delta G for that strand, within given constraints. A detailed study of the convergence behavior of the algorithm is conducted and various cooling schedules are investigated. An evaluation of the performance of the new algorithm in terms of prediction accuracy is made via comparison with the dynamic programming algorithm enfold for eight individual known structures from three RNA classes (SS rRNA, Group I intron 16S rRNA and 16S rRNA). The significant contribution of this algorithm is in showing comparable results with the most common dynamic programming prediction application mfold and surpassing results from an Evolutionary Algorithm (EA).

引用

页码：466 / +

页数：3

共 50 条

[21] Bayesian statistical algorithm for RNA secondary structure prediction
Division of Molecular Medicine, Wadsworth Ctr., New York State D., Albany, NY 12201-0509, United States
Comput. Chem., 3 (387-400):
[22] RnaPredict - An evolutionary algorithm for RNA secondary structure prediction
Wiese, Kay C.
Deschenes, Alain A.
Hendriks, Andrew G.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS, 2008, 5 (01) : 25 - 41
[23] A statistical sampling algorithm for RNA secondary structure prediction
Ding, Y
Lawrence, CE
NUCLEIC ACIDS RESEARCH, 2003, 31 (24) : 7280 - 7301
[24] An improved simulated annealing algorithm and its application to protein structure prediction
Guo, Chonghui
Zhu, Ping
Tang, Huanwen
Lu, Mingyu
WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 280 - 280
[25] An improved Parallel Simulated Annealing algorithm used for protein structure prediction
Liu, Yun-Ling
Tao, Lan
PROCEEDINGS OF 2006 INTERNATIONAL CONFERENCE ON MACHINE LEARNING AND CYBERNETICS, VOLS 1-7, 2006, : 2335 - +
[26] Improvement of simulated annealing algorithm and its application to protein structure prediction
Jin, Li-Xia
Tang, Huan-Wen
Xitong Gongcheng Lilun yu Shijian/System Engineering Theory and Practice, 2002, 22 (09): : 92 - 96
[27] Structural Prediction of RNA Loops by Simulated Annealing
Gohil, Mahendra Kumar
Chakraborty, Arindam
Savitha, G.
Dasgupta, Bhaskar
2019 16TH IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL INTELLIGENCE IN BIOINFORMATICS AND COMPUTATIONAL BIOLOGY - CIBCB 2019, 2019, : 319 - 326
[28] The significance of thermodynamic models in the accuracy improvement of RNA secondary structure prediction using permutation-based simulated annealing
Tsang, Herbert H.
Wiese, Kay C.
2007 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION, VOLS 1-10, PROCEEDINGS, 2007, : 3879 - 3885
[29] Changing Range Bat Algorithm for RNA Secondary Structure Prediction
Cui, Zhihua
Cao, Yang
Li, Feixiang
Zhu, Zhuanghua
JOURNAL OF COMPUTATIONAL AND THEORETICAL NANOSCIENCE, 2015, 12 (08) : 1968 - 1971
[30] A n2 RNA SECONDARY STRUCTURE PREDICTION ALGORITHM
Nebel, Markus E.
Scheid, Anika
BIOINFORMATICS: PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON BIOINFORMATICS MODELS, METHODS AND ALGORITHMS, 2012, : 66 - 75

← 1 2 3 4 5 →