Abstract: The invention relates to a computer-implemented Bayesian inference method for performing Bayesian inference in a Bayesian network, which includes a continuous child node (3) and its discrete parent node (2) having two states. Being provided with a calibrated continuous probability distribution of the observations of the child node (3) for each of the two states of the parent node (2), the inferring for a new observation of the child node (3) for which the state of the parent node (2) is not known of the probability of at least a first state of the parent node (2) makes use of masses of portions of the probability distributions that depend on a locational relationship of the probability distributions and the value of the new observation. This may ensure that the inferred probability of the first state of the parent node (2) monotonically changes with monotonically changing values of the new observation.

Abstract: The present invention relates to certain target genes of the FOXO transcription factor family, which are markers for an oxidative stress state and can be used for inferring an oxidative stress state of a FOXO transcription factor element in the body of a medical subject. The invention further relates to methods for inferring an oxidative stress state of a FOXO transcription element and for inferring the activity of the FOXO/PI3K cellular signalling pathway based on expression levels of the target genes as well as products to perform the methods.