This work deals with the relationship between the Bayesian and the
maximum likelihood estimators in case of dependent observations. In case of
Markov chains, we show that the Bayesian estimator of the transition probabilities
is a linear function of the maximum likelihood estimator (MLE).
Environmental contamination of food is a
worldwide public health problem. Folate mediated one- carbon metabolism plays
an important role in epigenetic regulation of gene expression and mutagenesis.
Many contaminants in food cause cancer through epigenetic mechanisms and/or DNA
instability i.e. default methylation of uracil to thymine, subsequent to the
decrease of 5-methylte- trahydrofolate (5 mTHF) pool in the one-carbon
metabolism network. Evaluating consequences of an exposure to food contaminants
based on systems biology approaches is a promising alternative field of
investigation. This report presents a dynamic mathematical modeling for the
study of the alteration in the one-carbon metabolism network by environmental
factors. It provides a model for predicting “the impact of arbitrary
contaminants that can induce the 5 mTHF deficiency. The model allows for a
given experimental condition, the analysis of DNA methylation activity and
dumping methylation in the de novo pathway of DNA synthesis.