Jove
Visualize
Contact Us

Related Concept Videos

DNA Isolation01:24

DNA Isolation

DNA isolation protocols can be fast and straightforward or complex and time-consuming depending on the type and quality of DNA required for further processing. For example, plasmid DNA extraction is a bit more complicated than genomic DNA extraction because of the need for an appropriate lysis method to separate plasmid DNA from gDNA during isolation. However, for specific applications, such as long-range DNA sequencing that require a good yield of high- quality DNA samples, we need to follow...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Estimating mutation rates from paternity casework.

Forensic science international. Genetics·2008
Same author

Object-oriented Bayesian networks for complex forensic DNA profiling problems.

Forensic science international·2006
Same author

Identification and separation of DNA mixtures using peak area information.

Forensic science international·2006
Same author

Probabilistic expert systems for DNA mixture profiling.

Theoretical population biology·2003
Same author

Non-fatherhood or mutation? A probabilistic approach to parental exclusion in paternity testing.

Forensic science international·2001
Same author

Familial tendency to foetal loss analysed with Bayesian graphical models by Gibbs sampling.

Statistics in medicine·2000
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Experiment Video

Updated: Jun 13, 2026

Enhanced Genetic Analysis of Single Human Bioparticles Recovered by Simplified Micromanipulation from Forensic ‘Touch DNA’ Evidence
11:49

Enhanced Genetic Analysis of Single Human Bioparticles Recovered by Simplified Micromanipulation from Forensic ‘Touch DNA’ Evidence

Published on: March 9, 2015

Probabilistic expert systems for handling artifacts in complex DNA mixtures.

R G Cowell1, S L Lauritzen, J Mortera

  • 1Faculty of Actuarial Science and Insurance, Cass Business School, 106 Bunhill Row, London EC1Y 8TZ, UK. rgc@city.ac.uk

Forensic Science International. Genetics
|May 11, 2010
PubMed
Summary

This study introduces a probabilistic framework to analyze DNA mixture profiles, accounting for PCR artifacts like allelic dropout and stutter. This improves the evaluation of DNA evidence in forensic casework.

More Related Videos

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Related Experiment Videos

Last Updated: Jun 13, 2026

Enhanced Genetic Analysis of Single Human Bioparticles Recovered by Simplified Micromanipulation from Forensic ‘Touch DNA’ Evidence
11:49

Enhanced Genetic Analysis of Single Human Bioparticles Recovered by Simplified Micromanipulation from Forensic ‘Touch DNA’ Evidence

Published on: March 9, 2015

Rare Event Detection Using Error-corrected DNA and RNA Sequencing
10:36

Rare Event Detection Using Error-corrected DNA and RNA Sequencing

Published on: August 3, 2018

Area of Science:

  • Forensic Science
  • Genetics
  • Biostatistics

Background:

  • Interpreting DNA mixture profiles is challenging due to artifacts like allelic dropout, stutter bands, and silent alleles.
  • Previous Bayesian network approaches often overlooked these common PCR-generated artifacts.

Purpose of the Study:

  • To develop a coherent probabilistic framework for interpreting STR DNA profiles from mixtures.
  • To incorporate artifacts such as allelic dropout, stutter bands, and silent alleles into the analysis.
  • To enhance the evaluation of evidential strength for DNA presence in mixtures.

Main Methods:

  • Utilized peak size information from PCR analysis of STR DNA profiles.
  • Extended an existing Bayesian network model to include artifact modeling.
  • Applied the framework to a published casework example for illustration.

Main Results:

  • The developed framework provides a more comprehensive approach to STR DNA mixture interpretation.
  • Successfully accounted for allelic dropout, stutter bands, and silent alleles.
  • Demonstrated improved evaluation of evidential strength compared to previous methods.

Conclusions:

  • The probabilistic framework offers a robust method for interpreting complex DNA mixtures in forensic science.
  • Accounting for PCR artifacts significantly improves the accuracy of DNA evidence evaluation.
  • The extended Bayesian network approach is valuable for casework analysis.