Landmark Pre-College Program in Computational Biology Launching Summer 2019
The Computational Biology Department has developed a Pre-College Program in Computational Biology to offer an immersive educational experience in computational biology accessible to high school students. Spearheaded by Drs. Phillip Compeau and Joshua Kangas, the program will provide training in both modern biology laboratory techniques and the computational analysis of the data generated by these experiments.
As part of the Pre-College Program in Computational Biology, students will collect water samples from Pittsburgh’s Three Rivers and apply a variety of techniques to study the bacterial populations (called the “microbiome”) of these rivers, which can vary based on season and water conditions. How can we isolate a single organism in this sea of bacteria and sequence its genome? What questions can we answer about a bacterium if we know its genome? How do we differentiate the hundreds of different micro-organisms present in the water based only on their DNA? Can we use this information to build a “Tree of Life” indicating the evolutionary relationships between a collection of different species? If we take thousands of high-resolution microscopic cellular images, can we train a computer to quickly analyze these images for us?
Students will learn that all of these fundamental questions can only be answered using high-powered computational approaches. As such, the Pre-College Program in Computational Biology will offer students a view of modern biological research that is not typically present in most high school curricula and that will prepare them well for their undergraduate studies.
The Pre-College Program in Computational Biology will run for three weeks starting in early July 2019. Applications will be accepted for both residential and commuter students starting November 1, 2018. There are limited opportunities for fee waivers. Students from underrepresented backgrounds as well as the greater Pittsburgh region are particularly encouraged to apply.