[1] Xie Xueying, Sun Xiao, Lu Zuhong,. Auto-selection order of Markov chain forbackground sequences with chi-square test [J]. Journal of Southeast University (English Edition), 2003, 19 (4): 311-316. [doi:10.3969/j.issn.1003-7985.2003.04.002]
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Auto-selection order of Markov chain forbackground sequences with chi-square test(
)
卡方检验确定背景序列模型Markov chain的阶数
)Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]
- Volumn:
- 19
- Issue:
- 2003 4
- Page:
- 311-316
- Research Field:
- Biological Science and Medical Engineering
- Publishing date:
- 2003-12-30
Info
- Title:
- Auto-selection order of Markov chain forbackground sequences with chi-square test
- 卡方检验确定背景序列模型Markov chain的阶数
- Author(s):
- Xie Xueying; Sun Xiao; Lu Zuhong
- Chien-Shiung Wu Laboratory, Southeast University, Nanjing 210096, China
- PACS:
- Q52
- DOI:
- 10.3969/j.issn.1003-7985.2003.04.002
- Abstract:
- Modeling non-coding background sequences appropriately is important for the detection of regulatory elements from DNA sequences. Based on the chi-square statistic test, some explanations about why to choose higher-order Markov chain model and how to automatically select the proper order are given in this paper. The chi-square test is first run on synthetic data sets to show that it can efficiently find the proper order of Markov chain. Using chi-square test, distinct higher order context dependences inherent in ten sets of sequences of yeast S.cerevisiae from other literature have been found. So the Markov chain with higher-order would be more suitable for modeling the non-coding background sequences than an independent model.
- 合理建模非编码序列对正确识别DNA序列中的调控元件非常重要.基于卡方统计检验, 给出了选用Markov chain模型来模拟序列背景分布的原因及如何确定Markov chain阶数的方法.卡方测试分析模拟数据发现它能有效地确定模型阶数.选择分析啤酒酵母中10类基因的上游序列集发现:所有序列集至少具有一阶以上的上下文相关性, 除1组基因外, 其余9组数据集具有二阶或三阶的上下文相关性.这说明用高阶Markov chain来建模背景序列比单碱基模型(零阶)更合理.
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Memo
- Memo:
- Biographies: Xie Xueying(1977—), female, graduate; Sun Xiao(corresponding author), male, doctor, professor, xsun@seu.edu.cn.