Fusion of laboratory and textual data for investigative bioforensics

Webb-Robertson, Bobbie-Jo M.; Corley, Courtney D.; McCue, Lee Ann; Wahl, Karen L.; Kreuzer, Helen

doi:10.1016/j.forsciint.2012.12.016

Cited by 6 publications

(8 citation statements)

References 30 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Its use has been seen to be gathering momentum over the past few years [28][29][30][31] in for example DNA profiling 32 , individualisation 33 , bioforensics 34 and forensic entomology 35 . This approach has also been applied to the forensic autopsy 36 which, whilst limited to prediction of cause of death from war victims, does illustrate the potential for an expert system to be used as a viable probabilistic tool for cases if appropriate information pertaining to the case was added to the system.…”

Section: Bayesian Statisticsmentioning

confidence: 99%

Post-mortem toxicology: A pilot study to evaluate the use of a Bayesian network to assess the likelihood of fatality

Langford

Bolton

Carlin

et al. 2015

Journal of Forensic and Legal Medicine

View full text Add to dashboard Cite

Northumbria University has developed Northumbria Research Link (NRL) to enable users to access the University's research output. Copyright © and moral rights for items on NRL are retained by the individual author(s) and/or other copyright owners. Single copies of full items can be reproduced, displayed or performed, and given to third parties in any format or medium for personal research or study, educational, or not-for-profit purposes without prior permission or charge, provided the authors, title and full bibliographic details are given, as well as a hyperlink and/or URL to the original metadata page. The content must not be changed in any way. Full items must not be sold commercially in any format or medium without formal permission of the copyright holder. The full policy is available online: http://nrl.northumbria.ac.uk/policies.html This document may differ from the final, published version of the research and has been made available online in accordance with publisher policies. To read and/or cite from the published version of the research, please visit the publisher's website (a subscription may be required.) Post-mortem Highlights• Systematic toxicological analysis should be routinely in death investigation.• Alternative approaches to using existing toxicological data should be considered.• Bayesian networks could be used in cases where drugs/drug combination are observed.• Influence of post-mortem redistribution requires further investigation. AbstractThe challenge of interpreting post-mortem drug concentrations is well documented and relies on appropriate sample collection, knowledge of case circumstances as well as reference to published tables of data, whilst taking into account the known issues of postmortem drug redistribution and tolerance. Existing published data has evolved from simple data tables to those now including sample origin and single to poly drug use, but additional information tends to be specific to those reported in individual case studies. We have developed a Bayesian network framework to assign a likelihood of fatality based on the contribution of drug concentrations whilst taking into account the pathological findings. This expert system has been tested against casework within the coronial jurisdiction of Sunderland, UK. We demonstrate in this pilot study that the Bayesian network can be used to proffer a degree of confidence in how deaths may be reported in cases when drugs are implicated. It has also highlighted the potential for deaths to be reported according to the pathological states at post-mortem when drugs have a significant contribution that may have an impact on mortality statistics. The Bayesian network could be used as complementary approach to assist in the interpretation of post-mortem drug concentrations.

show abstract

Section: Bayesian Statisticsmentioning

confidence: 99%

Post-mortem toxicology: A pilot study to evaluate the use of a Bayesian network to assess the likelihood of fatality

Langford

Bolton

Carlin

et al. 2015

Journal of Forensic and Legal Medicine

View full text Add to dashboard Cite

show abstract

“…Extending the Bayes net Webb-Robertson et al (2012) extended the Bayes net to predict likely institutions and even geographical regions where suspects may be present. By curating scientific literature, Webb-Robertson et al (2012) related culture media used to grow Bacillus species with those institutions where they were grown.…”

Section: 41mentioning

confidence: 99%

“…By curating scientific literature, Webb-Robertson et al (2012) related culture media used to grow Bacillus species with those institutions where they were grown. They identified over 2,469 documents with abstracts that mention a Bacillus species published between 2001 and 2011.…”

Section: 41mentioning

confidence: 99%

An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

Holmes¹,

Sego²,

Webb‐Robertson³

et al. 2013

View full text Add to dashboard Cite

“…The data obtained from these instruments yield features that, when integrated, create signatures indicative of the agent's identity and various aspects of how the agent was produced [1][2][3]. However, these instrument-driven analyses of the sample do not make a connection directly between the forensic signature and the potential source of the agent (i.e., suspect), although in some cases they might point to a region or institution [4,5]. It remains a challenge to link physical and genetic signatures to non-traditional sources of information to identify who and where the relevant source materials, equipment, and training exist to produce the sample.…”

Section: Introductionmentioning

confidence: 99%

“…The value of Bayesian networks to assist in investigations has been well established in the chemical and biological forensics fields [5][6][7][8][9][10][11]. Our previous work developed an automated Bayesian network framework to fuse the results of laboratory measurements with textual data associated with institutional capabilities to grow a specific organism under specific conditions [5].…”

Section: Introductionmentioning

confidence: 99%

Forensic Signature Detection of Yersinia pestis Culturing Practices across Institutions Using a Bayesian Network

Webb‐Robertson¹,

McCue²,

Clowers³

et al. 2014

J Forensic investig

View full text Add to dashboard Cite

The field of bioforensics is focused on the analysis of evidence from a biocrime. Existing laboratory analyses can identify the specific strain of an organism, as well signatures of the specific culture batch of organisms, such as low-frequency contaminants or indicators of growth and processing methods. To link these disparate types of physical data to potential suspects, investigators may need to identify institutions or individuals whose access to strains and culturing practices match those identified from the evidence. In this work, we present a Bayesian statistical network to fuse different types of analytical measurements that predict the production environment of a Yersinia pestis (Y. pestis) sample under investigation with automated text processing of scientific publications to identify institutions with a history of growing Y. pestis under similar conditions. Furthermore, the textual and experimental signatures were evaluated recursively to determine the overall sensitivity of the network across all levels of false positives. We illustrate that institutions associated with several specific culturing practices can be accurately selected based on the experimental signature from only a few analytical measurements. These findings demonstrate that similar Bayesian networks can be generated generically for many organisms of interest and their deployment is not prohibitive due to either computational or experimental factors.

show abstract

Fusion of laboratory and textual data for investigative bioforensics

Cited by 6 publications

References 30 publications

Post-mortem toxicology: A pilot study to evaluate the use of a Bayesian network to assess the likelihood of fatality

Post-mortem toxicology: A pilot study to evaluate the use of a Bayesian network to assess the likelihood of fatality

An Approach for Assessing the Signature Quality of Various Chemical Assays when Predicting the Culture Media Used to Grow Microorganisms

Forensic Signature Detection of Yersinia pestis Culturing Practices across Institutions Using a Bayesian Network

Contact Info

Product

Resources

About