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標題: 複式SELEX:隨機模式,模擬,及分析
Complex SELEX: Stochastic Modeling, Simulation and Analysis
作者: 趙佳琪
Chao, Chia-Chi
關鍵字: Complex SELEX;複式SELEX;Aptamer;Stochastic model;Simulations;適合體;隨機模型;電腦模擬
出版社: 應用數學系所
引用: References 1. Ellington, A.D. and J.W. Szostak, In vitro selection of RNA molecules that bind specific ligands. Nature, 1990. 346(6287): p. 818-22. 2. Tuerk, C. and L. Gold, Systematic evolution of ligands by exponential enrichment: RNA ligands to bacteriophage T4 DNA polymerase. Science, 1990. 249(4968): p. 505-10. 3. Tombelli, S., M. Minunni, and M. Mascini, Analytical applications of aptamers. Biosens Bioelectron, 2005. 20(12): p. 2424-34. 4. Burgstaller, P., A. Girod, and M. Blind, Aptamers as tools for target prioritization and lead identification. Drug Discov Today, 2002. 7(24): p. 1221-8. 5. Gold, L., The SELEX process: a surprising source of therapeutic and diagnostic compounds. Harvey Lect, 1995. 91: p. 47-57. 6. Green, L.S., et al., Inhibitory DNA ligands to platelet-derived growth factor B-chain. Biochemistry, 1996. 35(45): p. 14413-24. 7. Joshi, P.J., T.S. Fisher, and V.R. Prasad, Anti-HIV inhibitors based on nucleic acids: emergence of aptamers as potent antivirals. Curr Drug Targets Infect Disord, 2003. 3(4): p. 383-400. 8. Seiwert, S.D., et al., RNA aptamers as pathway-specific MAP kinase inhibitors. Chem Biol, 2000. 7(11): p. 833-43. 9. Sullenger, B.A., R.R. White, and C.P. Rusconi, Therapeutic aptamers and antidotes: a novel approach to safer drug design. Ernst Schering Res Found Workshop, 2003(43): p. 217-23. 10. Bier, F.F. and J.P. Furste, Nucleic acid based sensors. Exs, 1997. 80: p. 97-120. 11. Clark, S.L. and V.T. Remcho, Aptamers as analytical reagents. Electrophoresis, 2002. 23(9): p. 1335-40. 12. Hesselberth, J., et al., In vitro selection of nucleic acids for diagnostic applications. J Biotechnol, 2000. 74(1): p. 15-25. 13. Jayasena, S.D., Aptamers: an emerging class of molecules that rival antibodies in diagnostics. Clin Chem, 1999. 45(9): p. 1628-50. 14. Eaton, B.E., The joys of in vitro selection: chemically dressing oligonucleotides to satiate protein targets. Curr Opin Chem Biol, 1997. 1(1): p. 10-6. 15. Famulok, M., M. Blind, and G. Mayer, Intramers as promising new tools in functional proteomics. Chem Biol, 2001. 8(10): p. 931-9. 16. Nudler, E. and A.S. Mironov, The riboswitch control of bacterial metabolism. Trends Biochem Sci, 2004. 29(1): p. 11-7. 17. Burke, D.H. and J.H. Willis, Recombination, RNA evolution, and bifunctional RNA molecules isolated through chimeric SELEX. Rna, 1998. 4(9): p. 1165-75. 18. Irvine, D., C. Tuerk, and L. Gold, SELEXION. Systematic evolution of ligands by exponential enrichment with integrated optimization by non-linear analysis. J Mol Biol, 1991. 222(3): p. 739-61. 19. Weiqun Peng, et al., Dynamics of Competitive Evolution on a Smooth Landscape. PH YSICA L R EV I EW L ET T ERS, 2003. 90(8). 20. Yang, Y., H. Wang, and Q. Ouyang, Dynamics of DNA in vitro evolution with Mnt-repressor: simulations and analysis. Phys Rev E Stat Nonlin Soft Matter Phys, 2003. 68(3 Pt 1): p. 031903. 21. Vant-Hull, B., et al., The mathematics of SELEX against complex targets. J Mol Biol, 1998. 278(3): p. 579-97. 22. Daniels, D.A., et al., A tenascin-C aptamer identified by tumor cell SELEX: systematic evolution of ligands by exponential enrichment. Proc Natl Acad Sci U S A, 2003. 100(26): p. 15416-21. 23. Blank, M., et al., Systematic evolution of a DNA aptamer binding to rat brain tumor microvessels. selective targeting of endothelial regulatory protein pigpen. J Biol Chem, 2001. 276(19): p. 16464-8. 24. Morris, K.N., et al., High affinity ligands from in vitro selection: complex targets. Proc Natl Acad Sci U S A, 1998. 95(6): p. 2902-7. 25. Fields, D.S., et al., Quantitative specificity of the Mnt repressor. J Mol Biol, 1997. 271(2): p. 178-94. 26. Rosenwald, S., R. Kafri, and D. Lancet, Test of a statistical model for molecular recognition in biological repertoires. J Theor Biol, 2002. 216(3): p. 327-36. 27. Speed, T., statistical analysis of gene expression microarray data. interdisciplinary statistics series, ed. b.m. n.keiding, t. speed, p.van der heijden. 2003, new york: chapman & hall/crc. 28. Chen, C.-K. and T.-C. Kuo, Simulations of SELEX against Complex Targets with a Condensed Statistical Model. preprint, 2005.
指數富集的配體有系統演化(Systematic Evolution of Ligands by Exponential enrichment(SELEX))是一個在高度複雜的核酸分子庫中,以反覆的篩選及放大和目標分子(target)接合的配體(ligand)的一種重要的分子生物技術,而此與目標分子接合的配體我們稱之為適合體(aptamer)。近來在生物研究及藥品開發上,已提升至在核酸分子庫中同時挑選與多目標分子接合的配體實驗。為了了解此實驗,我們利用機率模型及電腦模擬來研究巨大配體母體的動態複式SELEX實驗的過程。模擬複式SELEX所得到的觀點不同於早期的平均場模型(mean field models)。我們假設隨機效應可能會影響分子庫在經過很多回合的篩選所得到最後的演化狀態。我們的計算方法也可以被應用在存在有其他競爭物質的巨大母體的演化研究上。

Systematic Evolution of Ligands by EXponential enrichment (SELEX) is an important technology in molecular biology of developing aptamers from highly complex nucleic acid library by iterative extraction and amplification of target-bound ligands. Recent advances in biological study and drug discovery have promoted the experiment to a higher level by simultaneously targeting the nucleic acid library with multiple targets: the complex SELEX. To gain insights of the experiment, we develop probabilistic model and simulation algorithm to investigate the dynamics of huge ligand population in the complex SELEX process. Our simulations have discovered aspects of complex SELEX not captured by early mean field models. We suggest that stochastic effects may prevent the library from converging to final states of evolution even in long rounds of screening. Our computation method can also be used to address problems in other research fields where the evolution of huge population is driven by the presence of some competitive members.
其他識別: U0005-2606200615404900
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