IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v101y2006p1323-1332.html
   My bibliography  Save this article

Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions

Author

Listed:
  • Yuan, Ming
  • Kendziorski, Christina

Abstract

No abstract is available for this item.

Suggested Citation

  • Yuan, Ming & Kendziorski, Christina, 2006. "Hidden Markov Models for Microarray Time Course Data in Multiple Biological Conditions," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 1323-1332, December.
    • Handle: RePEc:bes:jnlasa:v:101:y:2006:p:1323-1332
    as

    Download full text from publisher

    File URL: http://www.ingentaconnect.com/content/asa/jasa/2006/00000101/00000476/art00001
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sayantee Jana & Narayanaswamy Balakrishnan & Dietrich Rosen & Jemila Seid Hamid, 2017. "High dimensional extension of the growth curve model and its application in genetics," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(2), pages 273-292, June.
    2. Nanshan, Muye & Zhang, Nan & Xun, Xiaolei & Cao, Jiguo, 2022. "Dynamical modeling for non-Gaussian data with high-dimensional sparse ordinary differential equations," Computational Statistics & Data Analysis, Elsevier, vol. 173(C).
    3. Hamid Jemila S & Beyene Joseph, 2009. "A Multivariate Growth Curve Model for Ranking Genes in Replicated Time Course Microarray Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-26, July.
    4. Hou Jiayi & Archer Kellie J., 2015. "Regularization method for predicting an ordinal response using longitudinal high-dimensional genomic data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 14(1), pages 93-111, February.
    5. Zhang Yuping & Tibshirani Robert J. & Davis Ronald W., 2010. "Predicting Patient Survival from Longitudinal Gene Expression," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 9(1), pages 1-23, November.
    6. Lu Zhiheng K. & O. Brian Allen & Desmond Anthony F., 2012. "An Order Estimation Based Approach to Identify Response Genes for Microarray Time Course Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(6), pages 1-34, December.
    7. Vinciotti Veronica & Yu Keming, 2009. "M-quantile Regression Analysis of Temporal Gene Expression Data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 8(1), pages 1-20, September.
    8. Yueh-Yun Chi & Joseph G. Ibrahim & Anika Bissahoyo & David W. Threadgill, 2007. "Bayesian Hierarchical Modeling for Time Course Microarray Experiments," Biometrics, The International Biometric Society, vol. 63(2), pages 496-504, June.
    9. Yu Chuan Tai & Terence P. Speed, 2009. "On Gene Ranking Using Replicated Microarray Time Course Data," Biometrics, The International Biometric Society, vol. 65(1), pages 40-51, March.
    10. Yuan, Ming, 2006. "Flexible temporal expression profile modelling using the Gaussian process," Computational Statistics & Data Analysis, Elsevier, vol. 51(3), pages 1754-1764, December.
    11. Farcomeni Alessio & Arima Serena, 2012. "A Bayesian autoregressive three-state hidden Markov model for identifying switching monotonic regimes in Microarray time course data," Statistical Applications in Genetics and Molecular Biology, De Gruyter, vol. 11(4), pages 1-31, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:bes:jnlasa:v:101:y:2006:p:1323-1332. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.