Forensic Science International: Genetics
Volume 2, Issue 3 , Pages 166-175 , June 2008

Object-oriented Bayesian networks for paternity cases with allelic dependencies

  • Amanda B. Hepler

      Affiliations

    • Department of Statistical Science, University College London, Gower Street, London, WC1E 6BT, United Kingdom
    • Corresponding Author InformationCorresponding author. Tel: +44 20 7679 1624; fax: +44 20 7383 4703.
  • ,
  • Bruce S. Weir

      Affiliations

    • Department of Biostatistics, University of Washington, Box 357232, Seattle, WA 98195, United Kingdom

Received 29 October 2007 ,Accepted 1 December 2007.

References 

  1. Taroni F, Aitken C, Garbolino P, Biedermann A. Bayesian Networks and Probabilistic Inference in Forensic Science. Chichester: John Wiley and Sons; 2006;
  2. Weir BS. Effects of inbreeding on forensic calculations. Annu. Rev. Genet. 1994;28:597–621
  3. Curran JM, Buckleton JS, Triggs CM. What is the magnitude of the subpopulation effect?. Forensic Sci. Intl. 2003;135(1):1–8
  4. Curran JM, Buckleton JS. The appropriate use of subpopulation corrections for differences in endogamous communities. Forensic Sci. Intl. 2007;168(2–3):106–111
  5. Curran JM, Triggs CM, Buckleton JS, Weir BS. Interpreting DNA mixtures in structured populations. J. Forensic Sci. 1999;44(5):987–995
  6. Evett IW, Weir BS. Interpreting DNA Evidence. Sunderland, MA: Sinauer; 1998;
  7. Essen-Möller E. Die beweiskraft der ähnlichkeit im vaterschaftsnachweis: Theoretische grundlagen. Mitteilungen der Anthropologischen Gesellschaft. 1938;68:9–53
  8. Gill P, Foreman L, Buckleton JS, Triggs CM, Allen H. A comparison of adjustment methods to test the robustness of an STR DNA database comprised of 24 European populations. Forensic Sci. Intl. 2003;131:184–196
  9. Balding DJ, Nichols RA. DNA profile match probability calculation—how to allow for population stratification, relatedness, database selection and single bands. Forensic Sci. Intl. 1994;64(2–3):125–140
  10. National Research Council . The Evaluation of Forensic DNA Evidence. Washington, DC: National Academy Press; 1996;
  11. Balding DJ, Greenhalgh M, Nichols RA. Popullation genetics of STR loci in Caucasians. Int. J. Legal Med. 1996;108:300–305
  12. Buckleton JS, Curran JM, Walsh SJ. How reliable is the subpopulation model in DNA testimony. Forensic Sci. Intl. 2006;157:144–148
  13. Cowell RG, Dawid AP, Lauritzen SL, Spiegelhalter DJ. Probabilistic Networks and Expert Systems. Berlin-Heidelberg-New York: Springer-Verlag; 1999;
  14. Fenton N, Neil M. The jury observation fallacy and the use of Bayesian networks to present probabilistic legal arguments. Math. Today. 2000;36(6):180–187
  15. K. Korb, A. Nicholson, Bayesian Artificial Intelligence, Chapman & Hall CRC Press, Boca Raton, FL, 2004, Appendix B available at http://www.csse.monash.edu.au/bai/book/appendix_b.pdf.
  16. Evett IW, Gill PD, Jackson G, Whitaker J, Champod C. Interpreting small quantities of DNA: the hierarchy of propositions and the use of Bayesian networks. J. Forensic Sci. 2002;47(3):520–530
  17. Dawid AP, Mortera J, Pascali VL, Boxel DV. Probabilistic expert systems for forensic inference from genetic markers. Scand. J. Stat. 2002;29:577–595
  18. Mortera J. Analysis of DNA mixtures using Bayesian networks. In:  Green PJ,  Hjort NL,  Richardson S editor. Highly Structured Stochastic System. Oxford University Press; 2003;p. 39–44
  19. Aitken C, Taroni F, Garbolino P. A graphical model for the evaluation of cross-transfer evidence in DNA profiles. Theor. Popul. Biol. 2003;63:179–190
  20. Cowell RG. FINEX: A probabilistic expert system for forensic identification. Forensic Sci. Int. 2003;134:196–206
  21. Taroni F, Biedermann A, Garbolino P, Aitken C. A general approach to Bayesian networks for the interpretation of evidence. Forensic Sci. Int. 2004;139(1):5–13
  22. Biedermann A, Taroni F, Delemont O, Semadeni C, Davison A. The evaluation of evidence in the forensic investigation of fire incidents. Part 1: an approach using Bayesian networks. Forensic Sci. Int. 2005;147(1):49–57
  23. Taroni F, Bozza S, Biedermann A. Two items of evidence, no putative source: an inference problem in forensic intelligence. J. Forensic Sci. 2006;51(6):1350–1361
  24. Cavallini D, Corradi F. Forensic identification of relatives of individuals included in a database of DNA profiles. Biometrika. 2006;93(3):525–536
  25. Koller D, Pfeffer A. Object-oriented Bayesian networks. In: Proceedings of the 13th Annual Conference on Uncertainty in Artificial Intelligence (UAI-97). San Francisco, CA: Morgan Kaufmann; 1997;p. 302–331
  26. Laskey K, Mahoney S. Network fragments: representing knowledge for constructing probabilistic models. In: Proceedings of the 13th Annual Conference on Uncertainty in Artificial Intelligence (UAI-97). San Francisco, CA: Morgan Kaufmann; 1997;p. 334
  27. Dawid AP. An object-oriented Bayesian network for estimating mutation rates. ISBN 0-9727358-0-1 In:  Bishop CM,  Frey BJ editor. Ninth International Workshop on Artificial Intelligence and Statistics. Key West, Florida. 2003;
  28. A.P. Dawid,J. Mortera, P. Vicard, Object-oriented Bayesian networks for complex forensic DNA profiling problems, Forensic Sci. Int.169 (2–3) (2007) 195–205.
  29. Buckleton JS. Population genetic models. In:  Buckleton JS,  Triggs CM,  Walsh SJ editor. Forensic DNA Evidence Interpretation. Boca Raton, FL: CRC Press; 2005;p. 65–122
  30. Morris JW, Garber RA, d’Autremont J, Brenner CH. The avuncular index and the incest index. Adv. Forensic Haemogenet. 1988;1:607–611
  31. G.W. Beecham, Jr., B.S. Weir, Confidence interval of the likelihood ratio associated with mixed stain DNA evidence, J. Forensic Sci. (in press).

PII: S1872-4973(07)00403-6

doi: 10.1016/j.fsigen.2007.12.003

Forensic Science International: Genetics
Volume 2, Issue 3 , Pages 166-175 , June 2008