Biomedical subjects

Robert G Cowell

Publications and source records attributed to Robert G Cowell.

2 recordsLinked to original sources

PubMed2003

FINEX: a Probabilistic Expert System for forensic identification.

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.

Algorithms↗

PubMed2003

A clustering algorithm using DNA marker information for sub-pedigree reconstruction.

In a mass disaster scenario in which many people are dead, it may be that small family groups are among the dead, and investigators may need to identify such groups, e.g., to return bodies to living relatives for burial. We consider the problem of identifying small groups of closely related people within a large group of people through the use of DNA marker information. We propose a likelihood-ratio-based distance measure of the relatedness between pairs of individuals and use an estimate of this measure as a means of clustering related people into groups. We show the effectiveness of our approach on real examples and through simulations, which suggest that the method is quite reliable for identifying very close relationships. We discuss the use of our clustering algorithm in a two-stage pedigree reconstruction procedure and suggest directions in which the analysis could be extended. Applications include the identification of family groups among bodies found in mass graves and identification of family groups in animal populations.

Algorithms↗