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題名:結合基因演算法與模擬退火法於多重DNA序列之比對
書刊名:品質學報
作者:葉進儀 引用關係林軒仲
作者(外文):Yeh, Jinn-yiLin, Syuan-jhong
出版日期:2014
卷期:21:5
頁次:頁305-328
主題關鍵詞:序列比對多重序列比對基因演算法模擬退火法Sequence alignmentMultiple sequence alignmentGenetic algorithmsSimulated annealing
原始連結:連回原系統網址new window
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序列比對是將蛋白質中的基因或氨基酸進行對齊的動作,藉此找出兩序列的相似程度,而多重序列比對則是同時比對多個DNA或蛋白質序列,找出此序列群組中最佳的比對結果,本研究結合基因演算法及模擬退火法,先利用基因演算法物競天擇的概念,隨著世代演進逐漸產生近似最佳解,再利用模擬退火法進行小區塊內之比對修正,實驗結果顯示,利用基因演算法與模擬退火法之結合,使得基因演算法在跳脫局部最佳解的時候能有更大空間移動,而且也讓模擬退火法能有效解決經由基因演算法初步比對之後所產生的不良區域,此結合之序列比對結果比任何單一演算法的結果好,因此可以提升整體比對表現,將來能夠為生物學家在判斷未知序列功能時提供適當的輔助。
There was more and more DNA and protein sequence has been founded. The similar DNA sequence or protein sequence may have the same features. Therefore, sequence alignment has become the most popular technology in the field of bioinformatics. In this work, the combination of genetic algorithms and simulated annealing is used for multiple sequence alignment. Genetic algorithms apply the concept of fittest with evolution generation to gradually produce near optimal solutions. Simulated annealing is used to correct the alignment in small blocks. Experimental results show that the proposed method can let genetic algorithms' solutions to escape local optimum and to have more space to move, and also let simulated annealing effectively solves the problems with bad initial solutions generated by genetic algorithms. The results obtained by the proposed method are better than the results of any single algorithm. Therefore, the proposed method can improve the overall ratio of performance and will be able to provide appropriate support to biologists in determining the function of unknown sequence.
期刊論文
1.Chen, Shyi-Ming、Lin, Chung-Hui(20070600)。Multiple DNA Sequence Alignment Based on Genetic Simulated Annealing Techniques。International Journal of Information and Management Sciences,18(2),97-111。new window  new window
2.Edgar, R. C.、Batzoglou, S.(2006)。Multiple sequence alignment。Current Opinion in Structural Biology,16(3),368-373。  new window
3.Jangam, S. R.、Chakraborti, N.(2007)。A novel algorithm for DNA sequence alignment using ant colony optimization and genetic algorithms。Applied Soft Computing,7(3),1121-1130。  new window
4.Horng, J.-T.、Wu, L.-C.、Lin, C.-M.、Yang, B.-H.(2005)。A genetic algorithm for multiple sequence alignment。Soft Computing,9(6),407-420。  new window
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9.Notredame, C.(2002)。Recent progress in multiple sequence alignment: a survey。Pharmacogenomics,3(1),131-144。  new window
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16.Taylor, W. R.、Selensminde, G.、Eidhammer, I.(2000)。Multiple protein sequence alignment using double-dynamic programming。Computers and Chemistry,24(1),3-12。  new window
17.Wang, C.、Lefkowitz, E. J.(2011)。Genomic multiple sequence alignments: refinement using a genetic algorithm。BMC Bioinformatics,6,1471-2105。  new window
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21.Smith, Temple、Waterman, Michael(1981)。Identification of Common Molecular Subsequences。Journal of Molecular Biology,147(1),195-197。  new window
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會議論文
1.Huo, H.、Stojkovic, V.(2007)。A simulated annealing algorithm for multiple sequence alignment with guaranteed accuracy。Third International Conference on Natural Computation,270-274。  new window
2.Riaz, T.、Wang, Y.、Li, K.-B.(2004)。Multiple sequence alignment using Tabu search。Second Conference on Asia-Pacific Bioinformatics,223-232。  new window
學位論文
1.黃建彰(2008)。結合基因演算法及粒子群演算法於多重序列比對之研究(碩士論文)。義守大學。  延伸查詢new window
圖書
1.王聿泰、汪詩梅、范廷佳、許玉璇、陳淑美、黃彥華(2003)。生物資訊。臺北:教育部顧問室。  延伸查詢new window
2.李龍緣、林應如、許晉詮、萬磊、徐媛曼、洪千惠(2008)。生物資訊。臺北:九州圖書文物。  延伸查詢new window
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