I am
a Computer Science student in the Volgenau School of Engineering. This is my
second time as an undergrad; my first degree is in Sociology. Because of this,
I knew firsthand that getting involved on campus and looking for opportunities
beyond my coursework was important. Last summer I participated in a Research
Experience for Undergraduates (REU) program and came back to Mason interested
in doing more computer science research. I contacted Dr. Shehu, who runs
Mason’s Computational Biology Lab and she agreed to meet with me to discuss a
project she had in mind. As it turns out, she was the one who had promoted the
REU program I’d attended!
The
project I’m working on is a combination of supervised machine learning (ML) and
bioinformatics. Basically, I have several large datasets which contain all of
the possible formations a given protein molecule could take on. Each formation
is already labeled as being “near-native” (meaning it likely represents the
protein’s actual structure) or “non-native”. I’m testing different ML
algorithms to see whether we can accurately predict whether a protein is
“near-native” or not. This could help refine the way we predict protein
structure computationally, based on only its amino acid sequence (which is much
easier for chemists to determine than structure).
I
didn’t have any experience in this type of work before I started this project.
Dr. Shehu helped me get up to speed on the bioinformatics part of the project
last semester and this semester I also started working with Dr. Barbara, who is
a machine learning expert. Through this research project I’ve gained many
transferable skills including working with large datasets, using a
computing cluster, version control, and technical writing. These skills will be
useful long into my future career.
