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Bayesian hierarchical modelling for inferring genetic interactions in yeast

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Listed:
  • Jonathan Heydari
  • Conor Lawless
  • David A. Lydall
  • Darren J. Wilkinson

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Suggested Citation

  • Jonathan Heydari & Conor Lawless & David A. Lydall & Darren J. Wilkinson, 2016. "Bayesian hierarchical modelling for inferring genetic interactions in yeast," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 65(3), pages 367-393, April.
    • Handle: RePEc:bla:jorssc:v:65:y:2016:i:3:p:367-393
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    File URL: http://hdl.handle.net/10.1111/rssc.12126
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    References listed on IDEAS

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    1. Lin Zhang & Veerabhadran Baladandayuthapani & Bani K. Mallick & Ganiraju C. Manyam & Patricia A. Thompson & Melissa L. Bondy & Kim-Anh Do, 2014. "Bayesian hierarchical structured variable selection methods with application to molecular inversion probe studies in breast cancer," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 63(4), pages 595-620, August.
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    Cited by:

    1. Vinny Davies & Richard Reeve & William T. Harvey & Francois F. Maree & Dirk Husmeier, 2017. "A sparse hierarchical Bayesian model for detecting relevant antigenic sites in virus evolution," Computational Statistics, Springer, vol. 32(3), pages 803-843, September.
    2. Gholamhossein Barekat & Ali Moradi, 2018. "Recognition of Economic Growth Sources with Institutionalized Economics Approach," International Journal of Economics and Financial Issues, Econjournals, vol. 8(4), pages 265-270.

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