title: Probabilistic expert systems for DNA mixture profiling.
abstract: We show how probabilistic expert systems can be used to structure and solve complex cases of forensic identification involving DNA traces that might be mixtures of several DNA profiles. In particular, this approach can readily handle cases where the number of contributors to the mixture cannot be regarded as known in advance. The flexible modularity of the networks used also allows us to handle still more complex cases, for example where the finding of a mixed DNA trace is compounded by such features as missing individuals or the possibility of unobserved alleles.
authors.affiliation: Dipartimento di Economia, Università degli Studi Roma Tre, Via Ostiense 139, IT-00154 Rome, Italy. mortera@uniroma3.it
authors.forename: J
authors.initials: J
authors.lastname: Mortera
authors.forename: A P
authors.initials: AP
authors.lastname: Dawid
authors.forename: S L
authors.initials: SL
authors.lastname: Lauritzen
mesh_terms: D000483:Alleles; D001499:Bayes Theorem; D016172:DNA Fingerprinting / Q000379:methods / Q000706:statistics & numerical data*; D005103:Expert Systems; D005554:Forensic Medicine / Q000379:methods* / Q000706:statistics & numerical data; D006801:Humans; D011336:Probability; D006113:United Kingdom