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Cowell, R.; Lauritzen, S. L.; Mortera, J. (2009)
Publisher: Faculty of Actuarial Science & Insurance, City University London
Languages: English
Types: Article
Subjects: QA, QH426, HG
This paper presents a coherent probabilistic framework for taking account of allelic dropout, stutter bands and silent alleles when interpreting STR DNA profiles from a mixture sample using peak size information arising from a PCR analysis. This information can be exploited for evaluating the evidential strength for a hypothesis that DNA from a particular person is present in the mixture. It extends an earlier Bayesian network approach that ignored such artifacts. We illustrate the use of the extended network on a published casework example.

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