Protein 3D HP Model Folding Simulation Using a Hybrid of Genetic Algorithm and Particle Swarm Optimization

勤益科大機構典藏 > 電資學院 > 資訊工程系(所) > 【資訊工程系所】期刊論文 > Item 987654321/6885

請使用永久網址來引用或連結此文件: http://ir.lib.ncut.edu.tw/handle/987654321/6885

題名:	Protein 3D HP Model Folding Simulation Using a Hybrid of Genetic Algorithm and Particle Swarm Optimization
作者:	林正堅
貢獻者:	資訊工程系
日期:	2011-06
上傳時間:	2017-12-17 13:31:11 (UTC+8)
摘要:	Given the amino-acid sequence of a protein, the prediction of a protein's tertiary structure is known as the protein folding problem. The protein folding problem in the hydrophobic-hydrophilic lattice model is the problem of finding the lowest energy conformation. This is the NP-complete problem. In order to enhance the procedure performance for predicting protein structures, a hybrid genetic-based particle swarm optimization (PSO) is proposed. Simulation results indicate that our approach outperforms the existing evolutionary algorithms. The method can be applied successfully to the protein folding problem based on the three-dimensional hydrophobic- hydrophilic lattice model. © 2011 TFSA. (29 refs)
關聯:	International Journal of Fuzzy Systems
顯示於類別:	[資訊工程系(所)] 【資訊工程系所】期刊論文

文件中的檔案:

沒有與此文件相關的檔案.

檢視Licence

在NCUTIR中所有的資料項目都受到原著作權保護.