First and second order Markov posterior probabilities on multiple time-course data sets

Abstract

Development of models that explain relationships between changes in gene products often involve multiple replications of transcript abundance measurements across time courses. This paper develops a composite probabilistic analysis using a next-state paradigm. We not only consider the usual first-order Markov (next time step) setting but we also introduce a… (More)

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Cite this paper

@article{Norris2015FirstAS, title={First and second order Markov posterior probabilities on multiple time-course data sets}, author={James L. Norris and Kristopher L. Patton and Shengyuan Huang and David J. John and Gloria K. Muday}, journal={SoutheastCon 2015}, year={2015}, pages={1-8} }