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隐马模型及其在基因识别中的应用 被引量：2

Hidden Markov Models and Their Applications in Gene Finding
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摘要 生物信息学是一门新兴交叉学科,隐马模型是广泛用于该学科的数学模型.简要介绍了隐马模型的数学原理,并以大肠杆菌和人的基因识别为例说明了它在基因识别中的应用. Bioinformatics is a new cross-subject, and Hidden Markov models are widely used in it. In this paper, the mathematical theory of Hidden Markov models is briefly introduced, and tben the applications of them in gene finding are illustrated take examples for genes in Escherichia coli and Homo sapiens.
作者 曹胜玉 刘来福
机构地区 北京师范大学数学科学学院
出处 《数学的实践与认识》 CSCD 北大核心 2006年第9期212-218,共7页 Mathematics in Practice and Theory
关键词 生物信息学 隐马模型 基因识别 bioinformatics hidden markov models gene finding
分类号 Q811.4 [生物学—生物工程]
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  • 1[1]Sheynin,O.1988.A Markov's work on probability.Arch.Hist.Exact Sci.39:337-377.
  • 2[2]Blackwell,D.and Koopmans,L.1957.On the identifiable problem for functions of finite Markov chains.Ann.Math.Stat.28:1011-1015.
  • 3[3]Burke,C.J.and Rosenblatt,M.1958.A Markovian function of a Markov chain.Ann.Math.Stat.29:1112-1120.
  • 4[4]Gilbert,E.J.1959.On the identifiablity problem for functions of finite Markov chains.Ann.Math.Stat.30:688-697.
  • 5[5]Heller,A.1965.On stochastic processes derived from Markov chains.Ann.Math.Stat.36:1286-1291.
  • 6[6]Baum,L.E.,et al.1972.A maximization technique occurring in the statistical analysis of probabilistic functions of Markov chains.Ann.Math.Stat.41:164-171.
  • 7[7]Churchill,G.A.1989.Stochastic models for heterogeneous DNA sequences.Bull.Math.Biol.51:79-94.
  • 8[8]Stultz,C.M.,et al.1993.Structural analysis based on state-space modeling.Protein Sci.2:305-314.
  • 9[9]White,J.V.,et al.1994.Protein classification by stochastic modeling and optimal filtering of aminoacid sequences.Math.Biosci.119:35-75.
  • 10[10]Krogh,A.,et al.1994.Hidden Markov models in computational biology.Applications to protein modeling.J.Mol.Biol.235:1501-1531.

共引文献5

同被引文献22

  • 1杨乌日吐,李前忠,刘利,樊国梁.用支持向量机预测人类基因5′/3′选择性剪切位点[J].现代生物医学进展,2007,7(5):790-792. 被引量：2
  • 2DASH D, GOPALAKRISHNAN V. Modeling DNA splice regions by learning Bayesian networks[C]. CBMI Tech Report, 2001,11:33-40.
  • 3GUYON I, WESTON J, BARNHILL S, et al. Gene selection for cancer classification using support vector machines[J].Machine Learning, 2000, 46(1-3): 389-422.
  • 4SUN Y F, FAN X D, LI Y D. Identifying splicing sites in eukaryotic RNA: support vector machine approach [J].Computers in Biology and Medicine, 2003, 33:17- 29.
  • 5TONGLI C, QINKE P. Predicting the splice sites in DNA sequences using neural network based on complementary encoding method [C]//Proceedings of International Conference on Neural Networks. Beijing: IEEE Press, 2005,10(1):473-476.
  • 6杨文强,邓明华,钱敏平.隐马尔可夫模型与剪切位点识别[C]//中国运筹学会第六届学术交流会.中国:[s.n],2006.
  • 7LAFFERTY J, MCCALLUM A K, PEREIRA F. Conditional random fields: probabilistic models for segmenting and labeling sequence data[C]//In Proceedings of 18th International Conference on Machine Learning. [s.l.]:IEEE,2001.
  • 8POLLASTRO P, RAMPONE S. HS3D: homo sapiens splice site data set[J]. Nucleic Acids Research, Annual Database Issue ,2003,2:45-52.
  • 9BURSET M, GUIGO R. Evaluation of gene structure prediction programs[J]. Genomics, 1996, 34: 353-367.
  • 10ZHANG R. Evaluation of gene-finding algorithms by a content-balancing accuracy index[J].J Biomol Struct Dyn, 2002,19:1045-1052.

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数学的实践与认识
2006年 第9期

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