Dr. Catherine Grgicak joins OSAC’s Biology/DNA SAC as an Officer where she will aid in the development of national standards and guidelines from the Biological Methods, Biological Data Interpretation & Reporting and Wildlife Forensics Subcommittees.
LFTDI student and CIB PhD candidate, Nidhi Sheth, was awarded an NIJ (National Institute of Justice) Travel Grant to present her work “Deconvolution of Mixture Samples using Single-Cell Techniques for Forensic Human Identification” on March 03 at PITTCON Conference & Expo during the NIJ Poster Session.
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.
|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.|
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.
On Friday March 29, 2019, Dr. Grgicak will speak on topics related to Systems Thinking and the Impacts on Forensic Inference.
She shall summarize LFTDI’s work on the development of our computational systems which compute the a posteriori probability (APP) on the number of contributors (NoC) and the likelihood ratio (LR). Notably, she will highlight how the results from two computational systems may be combined in order to procure a complete weight-of-evidence. Last, she shall show how systematically optimizing the forensic laboratory process, using simulation, can improve LR outcomes and stabilize them across laboratories, improving inference outcomes nationally.
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 email@example.com, if interested by April 30th, 2019.
LFTDI acquires an Ion S5 and Chef NGS system for forensic applications. The technology will be used to build a dynamic model of the entire NGS pipeline, which will be used to optimize the NGS process for efficient and reliable forensic data generation in a cost effective manner.