Bayesian networks for victim identification on the basis of DNA profiles

C. J. Bruijning-van Dongen; K. Slooten; W. Burgers; W. Wiegerinck

doi:10.1016/j.fsigss.2009.08.024

Bayesian networks for victim identification on the basis of DNA profiles

C. J. Bruijning-van Dongen
, K. Slooten
, W. Burgers
, W. Wiegerinck

Mathematics

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

Abstract

We have developed software to improve screening and matching routine for victim identification based on DNA profiles. The software, called Napoleon/Bonaparte, uses Bayesian networks for the analysis. It is designed for effective handling of the identification process in case of a large disaster with many victims and can be applied in the missing person program. In this paper we will describe the Bayesian network approach and we will discuss some of the additional features to handle events with many victims. ?? 2009 Elsevier Ireland Ltd. All rights reserved.

Original language	English
Title of host publication	Forensic Science International: Genetics Supplement Series
Pages	466-468
Number of pages	3
DOIs	https://doi.org/10.1016/j.fsigss.2009.08.024
Publication status	Published - Jan 2009

Publication series

Name	Forensic Science International: Genetics Supplement Series
Volume	2

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Keywords

Bayesian networks
Computer programs
DNA profile
Forensic identification

Access to Document

10.1016/j.fsigss.2009.08.024

http://www.mendeley.com/research/bayesian-networks-victim-identification-basis-dna-profiles

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title = "Bayesian networks for victim identification on the basis of DNA profiles",

abstract = "We have developed software to improve screening and matching routine for victim identification based on DNA profiles. The software, called Napoleon/Bonaparte, uses Bayesian networks for the analysis. It is designed for effective handling of the identification process in case of a large disaster with many victims and can be applied in the missing person program. In this paper we will describe the Bayesian network approach and we will discuss some of the additional features to handle events with many victims. ?? 2009 Elsevier Ireland Ltd. All rights reserved.",

keywords = "Bayesian networks, Computer programs, DNA profile, Forensic identification",

author = "\{Bruijning-van Dongen\}, \{C. J.\} and K. Slooten and W. Burgers and W. Wiegerinck",

year = "2009",

month = jan,

doi = "10.1016/j.fsigss.2009.08.024",

language = "English",

isbn = "1875-1768",

series = "Forensic Science International: Genetics Supplement Series",

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Bayesian networks for victim identification on the basis of DNA profiles. / Bruijning-van Dongen, C. J.; Slooten, K.; Burgers, W. et al.
Forensic Science International: Genetics Supplement Series. 2009. p. 466-468 (Forensic Science International: Genetics Supplement Series; Vol. 2).

Research output: Chapter in Book / Report / Conference proceeding › Chapter › Academic › peer-review

TY - CHAP

T1 - Bayesian networks for victim identification on the basis of DNA profiles

AU - Bruijning-van Dongen, C. J.

AU - Slooten, K.

AU - Burgers, W.

AU - Wiegerinck, W.

PY - 2009/1

Y1 - 2009/1

N2 - We have developed software to improve screening and matching routine for victim identification based on DNA profiles. The software, called Napoleon/Bonaparte, uses Bayesian networks for the analysis. It is designed for effective handling of the identification process in case of a large disaster with many victims and can be applied in the missing person program. In this paper we will describe the Bayesian network approach and we will discuss some of the additional features to handle events with many victims. ?? 2009 Elsevier Ireland Ltd. All rights reserved.

AB - We have developed software to improve screening and matching routine for victim identification based on DNA profiles. The software, called Napoleon/Bonaparte, uses Bayesian networks for the analysis. It is designed for effective handling of the identification process in case of a large disaster with many victims and can be applied in the missing person program. In this paper we will describe the Bayesian network approach and we will discuss some of the additional features to handle events with many victims. ?? 2009 Elsevier Ireland Ltd. All rights reserved.

KW - Bayesian networks

KW - Computer programs

KW - DNA profile

KW - Forensic identification

U2 - 10.1016/j.fsigss.2009.08.024

DO - 10.1016/j.fsigss.2009.08.024

M3 - Chapter

SN - 1875-1768

T3 - Forensic Science International: Genetics Supplement Series

SP - 466

EP - 468

BT - Forensic Science International: Genetics Supplement Series

ER -

Bayesian networks for victim identification on the basis of DNA profiles

Abstract

Publication series

UN SDGs

Keywords

Access to Document

Persistent URL (handle)

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Cite this