Detecting similar high-dimensional responses to experimental factors between human and model organism

Reference:

Tommi Suvitaival, Ilkka Huopaniemi, Matej Orešic, and Samuel Kaski. Detecting similar high-dimensional responses to experimental factors between human and model organism. In NIPS 2011 workshop "From Statistical Genetics to Predictive Models in Personalized Medicine", to appear. Extended abstract.

Abstract:

We present a Bayesian model for analysing the effect of multiple experimental factors in two-species studies without the requirement of a priori known matching. From model studies of human diseases, conducted using *omics technologies and various model organisms, the question emerges: is there something similar in the molecular responses of the different organisms under certain conditions, such as healthy vs. diseased? Our approach provides a generative model for the task of analysing multi-species data, naturally taking into account the additional information about the affecting factors such as gender, age, treatment, or disease status.

Suggested BibTeX entry:

@inproceedings{Suvitaival11nipspm,
    author = {Tommi Suvitaival and Ilkka Huopaniemi and Matej Ore{\v{s}}i{\v{c}} and Samuel Kaski},
    booktitle = {{NIPS} 2011 workshop "From Statistical Genetics to Predictive Models in Personalized Medicine"},
    language = {eng},
    note = {Extended abstract},
    title = {Detecting similar high-dimensional responses to experimental factors between human and model organism},
    year = {to appear},
}