LFTDI inventors acquire U.S. Patent on NOCIt technology

Patent US 10,504,614 B2 was issued to Dr. Grgicak & Dr. Lun et al. for their “Systems and Methods for Determining an Unknown Characteristic of a Sample”.

This patent describes the invention underlying NOCIt, the system that allows a full evaluation of the entire forensic DNA signal across all probable number of contributors.

Dr. Grgicak accepts NIST/NIJ invitation to join the Expert Working Group on Human Factors in Forensic DNA Interpretation

The Expert Working Group on Human Factors in Forensic DNA Interpretation is charged with conducting a scientific assessment on the effects of human factors in forensic DNA examination with the goal of recommending approaches to improve its practice and reduce the likelihood of errors. The Working Group will evaluate relevant bodies of scientific literature and technical knowledge to develop its recommendations and will publish a report of its findings. 

Dr. Grgicak is honored to be part of this group and looks forward to participating.

LFTDI Presents Developmental Validation of NOCIt at NEAFS

Integrating Validated A Posteriori Probabilities on the Number of Contributors into Forensic Interpretation Pipelines for Full DNA Profile Interpretation will be presented at the 2019 NEAFS conference in Lancaster PA by Dr. Catherine M. Grgicak.

Here she will summarize the developmental validation of NOCIt – a software that renders the a posteriori probability distribution on the number of contributors to complex DNA mixtures – with a large-scale forensically relevant dataset. Notably, Dr. Grgicak shall demonstrate how the APP is used to calculate a full weight-of-evidence (log likelihood ratio or LR) without the need to designate that a particular NOC explains the evidence.

LFTDI Awarded NIST Grant to Develop In Silico MPS Forensic Laboratory

Dr. Grgicak was awarded a two-year grant from the NIST Measurement Science & Engineering Grant Program to develop an in silico NGS forensic laboratory.
The goal is to develop an in silico forensic laboratory using forensically relevant next-generation sequencing data in order to test multifarious laboratory scenarios and optimize processing decisions, improving forensic validation procedures. These in silico data can also be used to train machine learning and deep learning tools that require robust and large training sets, enhancing forensic analysis and interpretation procedures.

LFTDI M.S. Students Present Their Thesis Research

OPEN FORUM: SCI 114 (Chemistry Conference Room).

On Thursday April 25th at 3pm, come see Amanda present her work on: DEVELOPING A FORENSICALLY RELEVANT SINGLE-CELL INTERPRETATION STRATEGY FOR HUMAN IDENTIFICATION.
In this work Amanda demonstrates that single-cell signal is fundamentally different than signal acquired from bulk-processing, signifying new interpretation constructs are needed for forensically relevant single-cell signal.

On Monday April 29th at 5pm, come see Laura present her work on: STABILIZING INFORMATION CONTENT IN DNA EVIDENCE FOR IMPROVED LAB-TO-LAB INFERENCE
Laura shows that the information content in forensic electropherograms (EPGs) can drastically be improved by applying a simulation-experimental based approach. She then applies these improved post-PCR laboratory parameters to  optimize the pre-PCR process.

LFTDI Part-time Job Opening for M.S. Students: Research Assistant

M.S.-level Job Description:

  • M.S. level Part-time Research Assistant open to all Plan A (thesis-track) enrolled M.S. or 4th-Year B.S./M.S. Students in Chemistry, Biochemistry, Biology or Forensic Sciences.
  • Starts Fall 2019.
  • $12/hour; flexible 15-20 hours/week.
  • Up to 2 years.
  • Data may be used toward M.S. thesis, if applicable.
  • Training in and duties include, nucleic acid extraction, qPCR, PCR, dPCR, Capillary Electrophoresis, Next-Generation Sequencing and Data Analysis.
  • Preferred candidates will have taken, or plan to take, courses in Biochemistry, Bio-analytical/Molecular Biology, Statistics & Genetics.
  • Send C.V. to Dr. Catherine Grgicak at c.grgicak@rutgers.edu, if interested by April 30th, 2019.