The PACE™ software introduces a fully continuous, machine learning tool to the forensic DNA community that enables fast and accurate artifact management and predicts the number of contributors (NOC) in complex DNA mixtures. With NIJ backing, the researchers at Syracuse University’s Forensic and National Security Sciences Institute were able to reach numerous crime laboratories and stakeholders to gain valuable insight that accelerated the technology on the path to commercialization. Syracuse University has licensed the software to NicheVision Forensics, which also funded further development and has made the product available to the community. The PACE™ tool (Probabilistic Assessment for Contributor Estimation) is now available as software that is tailored toward the end user and can be seamlessly integrated into crime laboratory workflows.
The webinar will highlight the capacity of PACE™ to:
- Estimate the number of contributors in a matter of seconds, eliminating a critical, time-intensive data-interpretation step that is contributing to growing backlog issues.
- Enable analysts to arrive at more confident conclusions by generating number of contributor estimates based on tested machine learning models and serves as a quality control measure in the analysis of complex data.
- Manage artifacts by automating the identification of artifacts and subsequent correction, remove the effects of spectral overlap, and comprehensively model traditional and non-traditional stutter.
- Accommodate different DNA profiling kits and runs on standard computers, facilitating broader adoption that can be seamlessly integrated into existing workflows.