Jung-Wook Bang

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Multivariate metabolic profiles from biofluids such as urine and plasma are highly indicative of the biological fitness of complex organisms and can be captured analytically in order to derive top-down systems biology models. The application of currently available modeling approaches to human and animal metabolic pathway modeling is problematic because of(More)
Bayesian networks are constructed under a conditional independency assumption. This assumption however does not necessarily hold in practice and may lead to loss of accuracy. We previously proposed a hidden node methodology whereby Bayesian networks are adapted by the addition of hidden nodes to model the data dependencies more accurately. Empirical results(More)
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