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A Bayesian Approach to DNA Sequence Segmentation

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  • Richard J. Boys
  • Daniel A. Henderson

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  • Richard J. Boys & Daniel A. Henderson, 2004. "A Bayesian Approach to DNA Sequence Segmentation," Biometrics, The International Biometric Society, vol. 60(3), pages 573-581, September.
    • Handle: RePEc:bla:biomet:v:60:y:2004:i:3:p:573-581
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    File URL: http://hdl.handle.net/10.1111/j.0006-341X.2004.00206.x
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    References listed on IDEAS

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    1. C. P. Robert & T. Rydén & D. M. Titterington, 2000. "Bayesian inference in hidden Markov models through the reversible jump Markov chain Monte Carlo method," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(1), pages 57-75.
    2. Chib, Siddhartha, 1996. "Calculating posterior distributions and modal estimates in Markov mixture models," Journal of Econometrics, Elsevier, vol. 75(1), pages 79-97, November.
    3. Robert, Christian P. & Celeux, Gilles & Diebolt, Jean, 1993. "Bayesian estimation of hidden Markov chains: a stochastic implementation," Statistics & Probability Letters, Elsevier, vol. 16(1), pages 77-83, January.
    4. Matthew Stephens, 2000. "Dealing with label switching in mixture models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 795-809.
    5. R. J. Boys & D. A. Henderson & D. J. Wilkinson, 2000. "Detecting homogeneous segments in DNA sequences by using hidden Markov models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 49(2), pages 269-285.
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    Citations

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    Cited by:

    1. Hilary S. Booth & Conrad J. Burden & John H. Maindonald & Lucia Santoso & Matthew J. Wakefield & Susan R. Wilson, 2005. "Discussion of “A Bayesian Approach to DNA Sequence Segmentation”," Biometrics, The International Biometric Society, vol. 61(2), pages 635-637, June.
    2. Rolando de la Cruz & Cristian Meza & Nicolás Narria & Claudio Fuentes, 2022. "A Bayesian Change Point Analysis of the USD/CLP Series in Chile from 2018 to 2020: Understanding the Impact of Social Protests and the COVID-19 Pandemic," Mathematics, MDPI, vol. 10(18), pages 1-15, September.
    3. Luigi Spezia, 2010. "Bayesian analysis of multivariate Gaussian hidden Markov models with an unknown number of regimes," Journal of Time Series Analysis, Wiley Blackwell, vol. 31(1), pages 1-11, January.
    4. Nur, Darfiana & Allingham, David & Rousseau, Judith & Mengersen, Kerrie L. & McVinish, Ross, 2009. "Bayesian hidden Markov model for DNA sequence segmentation: A prior sensitivity analysis," Computational Statistics & Data Analysis, Elsevier, vol. 53(5), pages 1873-1882, March.
    5. Gong Chen & Qing Zhou, 2010. "Heterogeneity in DNA Multiple Alignments: Modeling, Inference, and Applications in Motif Finding," Biometrics, The International Biometric Society, vol. 66(3), pages 694-704, September.
    6. Castro, Bruno M. & Lemes, Renan B. & Cesar, Jonatas & Hünemeier, Tábita & Leonardi, Florencia, 2018. "A model selection approach for multiple sequence segmentation and dimensionality reduction," Journal of Multivariate Analysis, Elsevier, vol. 167(C), pages 319-330.
    7. R. J. Boys & D. A. Henderson, 2005. "Discussion of "A Bayesian Approach to DNA Sequence Segmentation "," Biometrics, The International Biometric Society, vol. 61(2), pages 637-639, June.
    8. Wolfgang P. Lehrach & Dirk Husmeier, 2009. "Segmenting bacterial and viral DNA sequence alignments with a trans‐dimensional phylogenetic factorial hidden Markov model," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 58(3), pages 307-327, July.

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