Cross-Species Translation of Multi-way Biomarkers

  • Tommi Suvitaival
  • Ilkka Huopaniemi
  • Matej Orešič
  • Samuel Kaski
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6791)


We present a Bayesian translational model for matching patterns in data sets which have neither co-occurring samples nor variables, but only a similar experiment design dividing the samples into two or more categories. The model estimates covariate effects related to this design and separates the factors that are shared across the data sets from those specific to one data set. The model is designed to find similarities in medical studies, where there is great need for methods for linking laboratory experiments with model organisms to studies of human diseases and new treatments.


Bayesian inference cross-species modeling multi-way modeling translational modeling 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Tommi Suvitaival
    • 1
  • Ilkka Huopaniemi
    • 1
  • Matej Orešič
    • 2
  • Samuel Kaski
    • 1
    • 3
  1. 1.Department of Information and Computer Science, Helsinki Institute for Information Technology HIITAalto University School of ScienceFinland
  2. 2.VTT Technical Research Centre of FinlandFinland
  3. 3.Department of Computer Science, Helsinki Institute for Information Technology HIITUniversity of HelsinkiFinland

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