We've updated our Privacy Policy to make it clearer how we use your personal data.

We use cookies to provide you with a better experience. You can read our Cookie Policy here.


New Way to Analyze DNA Evidence Under Development

Want a FREE PDF version of This News Story?

Complete the form below and we will email you a PDF version of "New Way to Analyze DNA Evidence Under Development"

Technology Networks Ltd. needs the contact information you provide to us to contact you about our products and services. You may unsubscribe from these communications at any time. For information on how to unsubscribe, as well as our privacy practices and commitment to protecting your privacy, check out our Privacy Policy

Read time:

Desmond Lun, an associate professor and chair of the Department of Computer Science at Rutgers–Camden, is part of a collaborative research team that has been awarded a $1.7 million Army Research Office grant to create a software program based on a computational method for analyzing DNA evidence. Lun is working with researchers from Boston University and the Massachusetts Institute of Technology.

“We’ve been working on the methodology, now we’re going to create a software program for it,” says Lun, who began the project two years ago through funding from the National Institute of Justice.

The research is focused on finding a way to more accurately analyze DNA evidence at a crime scene. DNA can be found in human cells from blood, hair, and skin. When a forensic analyst takes a DNA sample from an object, the DNA from everyone who had contact with the object is potentially in the sample.

“It’s a big problem for crime labs that a significant portion of the DNA samples they receive arise from more than one contributor and there is no accepted way of determining the number of contributors to the sample,” Lun says. “That’s the problem that we’re solving with this new software. Before forensic scientists can determine anything else about the evidence, they must first know how many people contributed to a DNA sample.”

The computational method Lun is developing tries to accurately determine the likelihood that a certain number of contributors gave rise to a given sample.

“Our work to date essentially shows that this computational method works and that it delivers significantly higher accuracy than any other method,” Lun says. “It is quite computationally intensive, so now we want to get to a point at which a software program can run efficiently on a regular computer.”

In addition to his collaboration with Boston University and MIT researchers, Lun is working with two Rutgers–Camden graduate students in computer science, Abhishek Garg and Anurag Arnold, as well as Harish Swaminathan, a doctoral student studying computational and integrative biology at Rutgers –Camden. Swaminathan was recently awarded a prestigious graduate research fellowship from the National Institute of Justice to help fund his work on the project.

The award program provides funding for research on crime, violence, and other criminal justice-related topics to accredited universities that support graduate study leading to research-based doctoral degrees.

“Our hope is that once it is developed, the software becomes the standard for crime labs everywhere,” Lun says.

A Philadelphia resident, Lun received bachelor’s degrees in mathematics and computer engineering from the University of Melbourne, Australia, and earned his master’s degree and doctoral degree from MIT.