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博碩士論文 etd-0823104-175630 詳細資訊
Title page for etd-0823104-175630
論文名稱
Title
利用遺傳演算法設計最佳多重聚合酶連鎖反應之引子
Multiplex PCR Primer Design Using Genetic Algorithm
系所名稱
Department
畢業學年期
Year, semester
語文別
Language
學位類別
Degree
頁數
Number of pages
38
研究生
Author
指導教授
Advisor
召集委員
Convenor
口試委員
Advisory Committee
口試日期
Date of Exam
2004-06-18
繳交日期
Date of Submission
2004-08-23
關鍵字
Keywords
多重聚合酶連鎖反應、引子設計、基因演算法
Primer Design, Multiplex PCR, Genetic Algorithm (GA)
統計
Statistics
本論文已被瀏覽 5662 次,被下載 2484
The thesis/dissertation has been browsed 5662 times, has been downloaded 2484 times.
中文摘要
多重聚合酶連鎖反應實驗是使用多對不同的引子組,於一次聚合酶連鎖反應中同時複製多段的DNA片段。近年來,雖然已有許多研究者針對設計聚合酶連鎖反應實驗所需的引子提出許多方法,但是其中只有少數是針對多重聚合酶連鎖反應實驗。因為要在同時間滿足數個不同的限制,而讓這個問題變成一項非常困難問題。但對於能有效設計出適合多重聚合酶連鎖反應的引子之策略仍然很少。本論文中,藉著使用遺傳演算法來設計多重聚合酶連鎖反應所需之多對引子組。此演算法可以更有效率的找出適合多重聚合酶連鎖反應所需之多對引子組,我們並提出一個MAP model,來使引子單一性的檢測能更快速。在dry-dock實驗中,我們可找到適合可用的多對引子用在多重聚合酶連鎖反應實驗,而且滿足設計條件與具有單一性的引子組。
Abstract
The multiplex PCR experiment is to amplify multiple regions of a DNA sequence at the same time by using different primer pairs. Although, in recent years, there are lots of methods for PCR primer design, only a few of them focus on the multiplex PCR primer design. The multiplex PCR primer design is a tedious task since there are too many constraints to be satisfied. A new method for multiplex PCR primer design strategy using genetic algorithm is proposed. The proposed algorithm is able to find a set of suitable primer pairs more efficient and uses a MAP model to speed up the examination of the specificity constraint. The dry-dock experiment shows that the proposed algorithm finds several sets of primer pairs for multiplex PCR that not only obey the design properties, but also have specificity.
目次 Table of Contents
Chapter 1. Introduction…1

Chapter 2. Background materials and literature reviews…4
2.1. Background materials…4
2.1.1 PCR and applications of PCR…4
2.1.2 Genetic algorithm…5
2.2 Literature reviews…7

Chapter 3. Definition of the constraints on multiplex PCR…9
3.1 The PCR constraints…9
3.2 Constraints of multiplex PCR…16

Chapter 4. The proposed algorithm…20
4.1 Initialization…20
4.2 Evaluation…22
4.3 Selection…24
4.4 Crossover…25
4.5 Mutation…25

Chapter 5. Dry dock experiments…26

Chapter 6. Discussion…33

Chapter 7. Conclusions…36

References…37
參考文獻 References
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[2] C. R. Newton and A. Graham (1997) PCR: Second Edition. Information Press, Etnsham,Oxon, UK.
[3] F. Meyer, C. Schleiermacher, and R. Giegerich (1995) Genefisher software support for the detection of postulated genes. http://bibiserv.techfak .uni-bielefeld.de/ docs/gf_paper.html.
[4] T. M. Rose, E. R. Schultz, J. G. Henikoff, S. Pietrokovski, C. M. McCallum, and S. Henikoff (1998) Consensus-degenerate hybrid oligonucleotide primers for amplification of distantly-related sequences. Nucleic Acids Res., Vol. 26, No. 7, pp.1628-1635.
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[6] S. E. Lincoln, M. J. Daly and E. S. Lander (1991) PRIMER: A Computer Program for Automatically Selecting PCR Primers. MIT Center for Genome Research and Whitehead Institute for Biomedical Research, Cambridge, Massachusetts.
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[8] P. Nicodème and J. Steyaert. (1997) Selecting optimal oligonucleotide primers for multiplex PCR. Intelligent Syst. Mol. Biol. Vol. 51, pp. 210-213.
[9] R. Schoske , P. M. Vallone, C. M. Ruitberg and J. M. Butler, (2003) Multiplex PCR design strategy used for the simultaneous amplification of 10 Y chromosome short tandem repeat (STR) loci. Anal. Bioanal. Chem., Vol. 375, pp. 333-343.
[10] T. Kämpke, M. Kieninger, and M. Mecklenburg. (2001) Efficient primer design algorithms, Bioinformatics, Vol. 17, pp. 214-225.
[11] D. E. Goldberg. (1989) Genetic Algorithms in Search, Optimization, and Machine Learning. Addison-Wesley, New York.
[12] K. D. Jong (1988) Learning with genetic algorithms: an overview. Machine Learning 3. Kluwer Academic, Hingham, MA. pp. 121-138.
[13] S. I. Fujita, Y. Senda, S. Nakaguchi and T. Hashimoto (2001) Multiplex PCR using internal transcribed spacer 1 and 2 regions for rapid detection and identification of yeast strains. J Clin Microbiol. Vol. 39. pp. 3617-3622.
[14] J. S. Wu, C. N. Lee, C. C. Wu and Y. L. Shiue (2004) Primer Design Using Genetic Algorithm, Bioinformatics, Vol. 20, pp. 1710-1717.
[15] N. C. Arbour, E. Lorenz, B. C. Schutte, J. Zabner, J. N. Kline, M. Jones, K. Frees, J. L. Watt, and D. A. Schwartz (2000) A genetics basis for a blunted response to endotoxin in Humans. http://www.ncbi.nlm.nih.gov/entrez/.
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