Advertisement

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)

Abstract

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.

Keywords

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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Gholami, A.M., Fellenberg, K.: Cross-species common regulatory network inference without requirement for prior gene affiliation. Bioinformatics 26(8), 1082–1090 (2010)CrossRefGoogle Scholar
  2. 2.
    Huopaniemi, I., Suvitaival, T., Nikkilä, J., Orešič, M., Kaski, S.: Multivariate multi-way analysis of multi-source data. Bioinformatics 26, i391–i398 (2010)CrossRefGoogle Scholar
  3. 3.
    Huopaniemi, I., Suvitaival, T., Nikkilä, J., Orešič, M., Kaski, S.: Two-way analysis of high-dimensional collinear data. Data Mining and Knowledge Discovery 19(2), 261–276 (2009)CrossRefMathSciNetGoogle Scholar
  4. 4.
    Huopaniemi, I., Suvitaival, T., Orešič, M., Kaski, S.: Graphical multi-way models. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds.) ECML PKDD 2010. LNCS (LNAI), vol. 6321, pp. 538–553. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  5. 5.
    Le, H.S., Bar-Joseph, Z.: Cross species expression analysis using a Dirichlet process mixture model with latent matchings. In: Lafferty, J., et al. (eds.) Advances in Neural Information Processing Systems 23, pp. 1270–1278 (2010)Google Scholar
  6. 6.
    Lu, Y., Huggins, P., Bar-Joseph, Z.: Cross species analysis of microarray expression data. Bioinformatics 25(12), 1476–1483 (2009)CrossRefGoogle Scholar
  7. 7.
    Lucas, J., Carvalho, C., West, M.: A Bayesian analysis strategy for cross-study translation of gene expression biomarkers. Statistical Applications in Genetics and Molecular Biology 8(1), 11 (2009)CrossRefzbMATHMathSciNetGoogle Scholar
  8. 8.
    Mardia, K.V., Bibby, J.M., Kent, J.T.: Multivariate analysis. Academic Press, London (1979)zbMATHGoogle Scholar
  9. 9.
    Orešič, M., et al.: Dysregulation of lipid and amino acid metabolism precedes islet autoimmunity in children who later progress to type 1 diabetes. Journal of Experimental Medicine 205(13), 2975–2984 (2008)CrossRefGoogle Scholar
  10. 10.
    Tripathi, A., Klami, A., Orešič, M., Kaski, S.: Matching samples of multiple views. Data Mining and Knowledge Discovery (2011)Google Scholar

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

Personalised recommendations