Just DNA Mixture Interpretation
In the fifth episode of Just Science, funded by the National Institute of Justice’s Forensic Technology Center of Excellence [Award 2016-MU-BX-K110], guest speaker Dr. Catherine Grgicak discusses DNA Mixture interpretation, currently a hot topic in forensic science. Dr. Grgicak and her colleagues at Boston University have developed tools and resources that are openly available to the forensic science community. This episode covers the CEESIt (Computational Evaluation of Evidentiary Signal) and NOCIt (Number Of Contributors) tools along with some of the other contributions that Dr. Grgicak and her colleagues have made to the forensic community. Listen and subscribe to learn more.
Dr. Grgicak (Gerg-i-chuck) is an Assistant Professor in the Biomedical Forensic Sciences Program at Boston University’s School of Medicine. She received her Bachelor of Science in Physical Sciences and Bachelor of Education from the University of Windsor, in Ontario Canada. She then went on to attain her Masters of Science in Forensic Sciences from the University of Alabama at Birmingham and Ph.D. in Chemistry from the University of Ottawa in Ontario Canada. She currently teaches courses in forensic DNA analysis and chemistry. Her forensic operations experience was obtained at the Alabama Department of Forensic Sciences in the CODIS unit and at Cellmark Diagnostics in Germantown MD. She is Executive Secretary of the OSAC subcommittee on Biological Data Interpretation and Reporting and is on the Editorial Board of the Journal of Forensic Sciences. Her current research focusses on analysis and interpretation of noisy signal from samples originating from complex environments.
If you wish to learn more, please visit Dr. Grgicak’s FTCOE Knowledge Transfer registration page click here.
NOCIt (Number Of Contributors): Outputs the a posteriori probability distribution for the number of contributors from which the sample arose. [Download Here] CEESIt (Computational Evaluation of Evidentiary Signal): Outputs the likelihood ratio, likelihood ratio distribution, and p-value for an unknown. [Download Here]
PROVEDIt publication (good for 50 days)