Literature DB >> 12689791

Probabilistic expert systems for DNA mixture profiling.

J Mortera1, A P Dawid, S L Lauritzen.   

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.

Mesh:

Year:  2003        PMID: 12689791     DOI: 10.1016/s0040-5809(03)00006-6

Source DB:  PubMed          Journal:  Theor Popul Biol        ISSN: 0040-5809            Impact factor:   1.570


  7 in total

1.  Estimating the number of contributors to a DNA profile.

Authors:  Thore Egeland; Ingvild Dalen; Petter F Mostad
Journal:  Int J Legal Med       Date:  2003-08-14       Impact factor: 2.686

2.  Automated DNA profile analysis.

Authors:  Eleanor A M Graham
Journal:  Forensic Sci Med Pathol       Date:  2005-12       Impact factor: 2.007

3.  An information gap in DNA evidence interpretation.

Authors:  Mark W Perlin; Alexander Sinelnikov
Journal:  PLoS One       Date:  2009-12-16       Impact factor: 3.240

4.  The genotypic structure of a multi-host bumblebee parasite suggests a role for ecological niche overlap.

Authors:  Rahel M Salathé; Paul Schmid-Hempel
Journal:  PLoS One       Date:  2011-08-10       Impact factor: 3.240

5.  CDMBE: A Case Description Model Based on Evidence.

Authors:  Jianlin Zhu; Xiaoping Yang; Jing Zhou
Journal:  Comput Intell Neurosci       Date:  2015-09-01

6.  TrueAllele casework on Virginia DNA mixture evidence: computer and manual interpretation in 72 reported criminal cases.

Authors:  Mark W Perlin; Kiersten Dormer; Jennifer Hornyak; Lisa Schiermeier-Wood; Susan Greenspoon
Journal:  PLoS One       Date:  2014-03-25       Impact factor: 3.240

7.  New York State TrueAllele ® casework validation study.

Authors:  Mark W Perlin; Jamie L Belrose; Barry W Duceman
Journal:  J Forensic Sci       Date:  2013-07-18       Impact factor: 1.832

  7 in total

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