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.