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Detecting similar high-dimensional responses to experimental factors from human and model organism
This video was recorded at NIPS Workshops, Sierra Nevada 2011. 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.
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This work is licensed under a Attribution-NonCommercial-NoDerivs 3.0 United States
