title: FINEX: a Probabilistic Expert System for forensic identification.
abstract: A series of recent papers have shown how to formulate complex problems of forensic DNA identification inference, such as occur in disputed paternity or criminal identification cases, in terms of Probabilistic Expert Systems (PESs). However, at the present time, general purpose PES software is not particularly well suited to the repetitive tasks of: specifying an appropriate set of marker networks for a specific problem; for editing the many local conditional probability tables; and combining evidence from several genetic markers to evaluate likelihoods. Here, I describe a user-friendly prototype software tool called FINEX developed both to automate such tasks and also to evaluate likelihoods of interest. Ease of use is achieved by a graphical specification language that enables a user to quickly specify a range of forensic DNA problems. I describe the algorithms by which FINEX converts the user input in the graphical specification language and data on observed markers to the Bayesian networks used in PES.
authors.affiliation: Faculty of Actuarial Science and Statistics, CASS Business School, City University London, 106 Bunhill Row, EC1V 8TZ London, UK. rgc@city.ac.uk
authors.forename: Robert G
authors.initials: RG
authors.lastname: Cowell
mesh_terms: D000465:Algorithms; D001499:Bayes Theorem; D016172:DNA Fingerprinting / Q000379:methods*; D005103:Expert Systems; D005554:Forensic Medicine / Q000379:methods*; D006801:Humans; D008297:Male; D010334:Paternity; D011336:Probability; D006113:United Kingdom