Bayesian statistics and gene regulations


We will discuss our recent work on using the methods of Bayesian statistics to infer gene regulations from time-course expression data. The model we developed performs smoothing of the data and fitting of the parameters in one step and informs the user about uncertainty associated with the parameters of the regulation. The talk will focus on the technical aspects of the work and demonstrate that with modern tools, fully Bayesian approach is feasible for challenging bioinformatics tasks.

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