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Research on Algorithms of Multiple Sequence Alignment Based on Iterative Strategy

Author: JinXin
Tutor: LuoZhiGang
School: National University of Defense Science and Technology
Course: Computer Science and Technology
Keywords: Bioinformatics Progressive multiple sequence alignment ClustalW Parallel computing The iteration than on strategy
CLC: TP399-C8
Type: Master's thesis
Year: 2007
Downloads: 72
Quote: 1
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Abstract


Multiple sequence alignment is one of the bioinformatics core research content . Through the multiple sequence alignment , biologists can conduct phylogenetic analysis , build family of proteins , RNA and protein structure prediction , helps more accurate in-depth analysis . Multiple sequence alignment problem of high computational complexity , has decided it can not use the standard dynamic programming algorithm theoretically optimal solution can only use heuristic strategies to get an approximate solution . Progressive multiple sequence alignment is the most widely used as a heuristic algorithm , the algorithm first by pairwise sequence between the comparison to determine distance matrix , and then determine a phylogenetic tree based on distance matrix Finally, based on the evolutionary tree in the size of the evolutionary distance gradual build multiple sequence alignment . However , the progressive multiple sequence than the existence of local minimization problem , than the result accuracy rate is not high ; calculation of high complexity limits its application to a certain extent . The focus of this project study the use of local information to improve the accuracy of the progressive alignment of the sequence , the main work is as follows : a detailed analysis of the current most widely used international progressive multiple sequence alignment algorithm The ClustalW , pointed out its problems : the local minimum , divergence and evolution from the non-uniform sequence of low accuracy . In response to these problems , we learn star ideological alignment and iterative comparison , proposed a new center sequence - based iterative optimization algorithm IS-ClustalW, First ClustalW to generate an initial comparison of results , and then the results according to the Centre to reconsider the order of the sequence twenty-two global alignment , iterative process based on the information twenty-two local alignment of multiple sequence than the result of correction . The test results show that , the the IS - The ClustalW The , accuracy is better than ClustalW, local minimization problem is solved to some extent . On this basis , the task partitioning strategy - based and multi-threaded parallel technology , the IS-ClustalW pairwise comparison , two stages parallel iterative optimization . The test results show that the algorithm has a good computing performance .

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