Forensic DNA signal is notoriously challenging to assess, requiring computational tools to support its interpre- tation. Over-expressions of stutter, allele drop-out, allele drop-in, degradation, differential degradation, and the like, make forensic DNA profiles too complicated to evaluate by manual methods. In response, computational tools that make point estimates on the Number of Contributors (NOC) to a sample have been developed, as have Bayesian methods that evaluate an A Posteriori Probability (APP) distribution on the NOC. In cases where an overly narrow NOC range is assumed, the downstream strength of evidence may be incomplete insofar as the evidence is evaluated with an inadequate set of propositions. In the current paper, ...
We present a statistical model for the quantitative peak information obtained from an electropherogr...
Machine learning obtains good accuracy in determining the number of contributors (NOC) in short tand...
Using machine learning to determine the number of contributors (NOC) in short tandem repeat (STR) mi...
Forensic DNA signal is notoriously challenging to assess, requiring computational tools to support i...
Forensic DNA signal is notoriously challenging to interpret and requires the implementation of compu...
In the forensic examination of DNA mixtures, the question of how to set the total number of contribu...
Forensic scientists are routinely faced with the problem of assessing the total number of contributo...
In traditional forensic DNA casework, the inclusion or exclusion of individuals who may have contr...
Forensic analysis of a deoxyribonucleic acid (DNA) profile includes determining if DNA from a known ...
Forensic samples containing DNA from two or more individuals can be difficult to interpret. Even asc...
DNA is now routinely used in criminal investigations and court cases, although DNA samples taken at ...
DNA is now routinely used in criminal investigations and court cases, although DNA samples taken at ...
We present a statistical model for the quantitative peak information obtained from an electropherogr...
Machine learning obtains good accuracy in determining the number of contributors (NOC) in short tand...
Using machine learning to determine the number of contributors (NOC) in short tandem repeat (STR) mi...
Forensic DNA signal is notoriously challenging to assess, requiring computational tools to support i...
Forensic DNA signal is notoriously challenging to interpret and requires the implementation of compu...
In the forensic examination of DNA mixtures, the question of how to set the total number of contribu...
Forensic scientists are routinely faced with the problem of assessing the total number of contributo...
In traditional forensic DNA casework, the inclusion or exclusion of individuals who may have contr...
Forensic analysis of a deoxyribonucleic acid (DNA) profile includes determining if DNA from a known ...
Forensic samples containing DNA from two or more individuals can be difficult to interpret. Even asc...
DNA is now routinely used in criminal investigations and court cases, although DNA samples taken at ...
DNA is now routinely used in criminal investigations and court cases, although DNA samples taken at ...
We present a statistical model for the quantitative peak information obtained from an electropherogr...
Machine learning obtains good accuracy in determining the number of contributors (NOC) in short tand...
Using machine learning to determine the number of contributors (NOC) in short tandem repeat (STR) mi...