Representing and solving complex DNA identification cases using Bayesian networks

Object-oriented Bayesian networks (OOBNs) can be used to model and solve a wide variety of complex forensic DNA identication problems, involving such complications as missing individuals, mutation, and null alleles. We provide a brief overview of the approach and illustrate its use. In particular, we investigate the effect on paternityratios of allowing for silent alleles, and show that this can be substantial even when the probability of silence is very small.