TY - GEN
T1 - A novel EDAs based method for HP model rotein folding
AU - Chen, Benhui
AU - Li, Long
AU - Hu, Jinglu
PY - 2009
Y1 - 2009
N2 - The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms (EDAs) based method to solve the PSP problem on HP model. Firstly, a composite fitness function containing the information of folding structure core formation is introduced to replace the traditional fitness function of HP model. It can help to select more optimum individuals for probabilistic model of EDAs algorithm. And a set of guided operators are used to increase the diversity of population and the likelihood of escaping from local optima. Secondly, an improved backtracking repairing algorithm is proposed to repair invalid individuals sampled by the probabilistic model of EDAs for the long sequence protein instances. A detection procedure of feasibility is added to avoid entering invalid closed areas when selecting directions for the residues. Thus, it can significant reduce the number of backtracking operation and the computational cost for long se quence protein. Experimental results demonstrate that the proposed method outperform the basic EDAs method. At the same time, it is very competitive with the other existing algorithms for the PSP problem on lattice HP models.
AB - The protein structure prediction (PSP) problem is one of the most important problems in computational biology. This paper proposes a novel Estimation of Distribution Algorithms (EDAs) based method to solve the PSP problem on HP model. Firstly, a composite fitness function containing the information of folding structure core formation is introduced to replace the traditional fitness function of HP model. It can help to select more optimum individuals for probabilistic model of EDAs algorithm. And a set of guided operators are used to increase the diversity of population and the likelihood of escaping from local optima. Secondly, an improved backtracking repairing algorithm is proposed to repair invalid individuals sampled by the probabilistic model of EDAs for the long sequence protein instances. A detection procedure of feasibility is added to avoid entering invalid closed areas when selecting directions for the residues. Thus, it can significant reduce the number of backtracking operation and the computational cost for long se quence protein. Experimental results demonstrate that the proposed method outperform the basic EDAs method. At the same time, it is very competitive with the other existing algorithms for the PSP problem on lattice HP models.
UR - http://www.scopus.com/inward/record.url?scp=70450137092&partnerID=8YFLogxK
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U2 - 10.1109/CEC.2009.4982963
DO - 10.1109/CEC.2009.4982963
M3 - Conference contribution
AN - SCOPUS:70450137092
SN - 9781424429592
T3 - 2009 IEEE Congress on Evolutionary Computation, CEC 2009
SP - 309
EP - 315
BT - 2009 IEEE Congress on Evolutionary Computation, CEC 2009
T2 - 2009 IEEE Congress on Evolutionary Computation, CEC 2009
Y2 - 18 May 2009 through 21 May 2009
ER -