Probabilistic modelling for DNA mixture analysis

TY - JOUR

T1 - Probabilistic modelling for DNA mixture analysis

AU - Cowell, R. G.

AU - Lauritzen, S. L.

AU - Mortera, J.

PY - 2008/8/1

Y1 - 2008/8/1

N2 - Taking peak area information into account when analysing STR DNA mixtures is acknowledged to be a difficult task. There have been a number of non-probabilistic approaches proposed in the literature, and some have been incorporated into computer systems, but comparatively little has been published from a probabilistic perspective. Here we briefly review our previous work on using Bayesian networks to analyse two-person mixtures within a probabilistic framework, and present preliminary results obtained for analysing two-person and three-person mixtures that combine peak area information from multiple independent samples.

AB - Taking peak area information into account when analysing STR DNA mixtures is acknowledged to be a difficult task. There have been a number of non-probabilistic approaches proposed in the literature, and some have been incorporated into computer systems, but comparatively little has been published from a probabilistic perspective. Here we briefly review our previous work on using Bayesian networks to analyse two-person mixtures within a probabilistic framework, and present preliminary results obtained for analysing two-person and three-person mixtures that combine peak area information from multiple independent samples.

KW - Bayesian networks

KW - DNA mixtures

KW - Multiple contributors

KW - Multiple traces

UR - http://www.scopus.com/inward/record.url?scp=50349100232&partnerID=8YFLogxK

U2 - 10.1016/j.fsigss.2007.10.087

DO - 10.1016/j.fsigss.2007.10.087

M3 - Journal article

AN - SCOPUS:50349100232

SN - 1875-1768

VL - 1

SP - 640

EP - 642

JO - Forensic Science International: Genetics. Supplement Series

JF - Forensic Science International: Genetics. Supplement Series

IS - 1

ER -