Leading the next generation of computational biologists
For the latest issue of FLG Magazine, we spoke to 17-year-old Prathik Naidu, a young man who is pioneering research and building a bright student future for translational bioinformatics.
What were you doing at 17? Chances are it wasn’t presenting at major scientific conferences, and helping to nurture future generations of scientists. Well, that’s exactly what Prathik Naidu, a high school senior from Thomas Jefferson High School for Science and Technology in VA, USA, is doing. As well as his involvement with the International Society for Computational Biology (ISCB), the high school junior has also spent two summers at Johns Hopkins University, and was one of a handful of students selected to participate in MIT’s Research Science Institute summer internship program. With an incredibly bright future ahead of him, we were fortunate enough to have an opportunity to speak with one of the field’s brightest young talents.
FLG: Where did your interest in bioinformatics come from?
PN: I used to be interested in wet lab work because I grew up doing hands-on experiments with my chemistry kit. I always thought that science entailed wearing a lab coat and goggles while carefully mixing chemicals in the lab. I took up a summer internship as a 9th grader, and found myself working on my laptop all day writing programs and analysing genetic sequences. I didn’t really expect science to be done this way, but it really got me fascinated with the whole field of computational biology and bioinformatics. After that, I just started to find more research projects to learn more.
FLG: Why do you think kids don’t think of computational work when they think of science?
PN: As a kid, you really like to mess around and get hands on with stuff. A lot of the science kits out there are geared around this, and the projects you do for science fairs in elementary and middle schools are based around these hands-on experiments. So I think that’s where the perception that science research entails working with chemicals in the lab comes from. Although I had some prior knowledge of computer science, I wasn’t exposed to the computational side of research until my internship at Johns Hopkins.
FLG: Could you talk us through your internships?
PN: My first internship was working on building some computational analysis algorithms to compare gene expression patterns between different ethnicities. I wanted to understand what those differences are, and how they might play a role in inherited diseases. It was some heavy computational work, but I was able to teach myself the fundamental programming skills needed in genetics research. After I finished the project, I had the opportunity to present my work at state science fairs where I won the grand prize. I was also a finalist in the computational biology category at the Intel International Science and Engineering Fair.
My next project was with a professor at Harvard Medical School, where I used statistical algorithms to identify changes in the mutation patterns across 31 different cancer types. We used statistical models to predict mutations that would commonly occur in specific cancer types, which can help with elucidating new mechanisms that might act as potential drug targets.
Finally, I applied for a summer programme at MIT’s Research Science Institute, which is an all-expenses paid 6-week internship for 52 students nation-wide. The project focused on using machine learning to predict how DNA forms 3D structures and how they can help understand changes in cancer cells. It was an intensive but rewarding experience, and I had the wonderful opportunity to meet with young scientists from around the world.
Find out more about Prathik’s work and projects on page 22!