I’m working at the Harvard Medical School Department of Systems Biology on a computational analysis of what is called the encode consortium dataset.
Ved Topkar, ‘16, has spent his summer exploring the intersection of two of his passions, biology and computer science, with Dr. Jeremy Gunawardena, professor in the Department of Systems Biology. Topkar is working in epigenetics, a field that studies changes in gene expression caused by factors other than genetic code. Brevia spoke with Topkar to learn more about his research.
Brevia: What kind of research have you been working on over the summer?
VT: I’m working at the Harvard Medical School Department of Systems Biology. What I’m working on a computational analysis of what is called the encode consortium dataset. Encode stands for the encyclopedia of DNA elements, and essentially since ’07 or so, there have been 430-plus labs around the world, mainly in the US, who have all worked together to basically create a large-scale database of epigenetic data.
Epigenetic data consists mainly of information about proteins and chemical modifications made to human DNA. There haven’t been too many large studies that go through all the data out there and try to find some unifying results for it, so that’s what I’m trying to do. In particular, I’m working with chronic myelogenous leukemia. Basically I’m looking at the promoters of all the genes in the human genome and looking at what transcription factors bind to these promoters and then trying to reduce all of these tens of thousands of promoters into categories.
Brevia: Do you feel that your interest in systems biology and this type of research is unique?
VT: I think what made me interested in systems biology in general is that I’ve liked biology for a long time, and I’ve also liked computer science for a long time. The application of quantitative methods to large scale data analysis is a very unique application of the intersection of computer science and biology. This kind of project required things that only both my interests could really do and only when they were put together.
I would say if I had done it ten years ago, it would be more unique than it is now. The reason why is just because we are in this new genomic age in which the only way that we can really seek or gain a more comprehensive understanding of biological systems given the technology we have is by collecting a lot of data and then figuring out what the data says, and that was a direct result of the Human Genome Project.
Brevia: How will future students, professors, and researchers benefit from your work?
VT: Right now what we are seeing is the traditional model in which researchers will choose one promoter or one gene or one protein that binds to one gene and they’ll say, “Here’s an isolated system of this one specific pathway.” That’s important because you choose that promoter or you choose that gene or protein because it has some specific implication.
But a limitation is that that is a very narrow scope because there are so many thousand genes and thousands of proteins and modifications and machinery that are constantly chugging along in the cell. There is no way that we can do that and gain a comprehensive understanding of the human system, so in particular what I’m trying to do is quantitatively classify promoters.
We have a quantitative metric that allows us to take any promoter and then put it in a category. We’re going by this very strict codified quantitative structure, and that’s important and useful because, as with any large and complex system, being able to objectively categorize, classify and codify things makes further analysis by the larger scientific community much more accessible. The other thing is continually trying to shift mindsets away from looking at only small systems to also considering both the small system and the larger system as a whole.
Brevia: What would be your advice to your fellow Harvard students?
VT: I’ve definitely been humbled by the experience of saying I know there is something out there in regards to what I want to do but I have no idea how to approach it. As Harvard students, we constantly want to know what is going on and know what is next, but sometimes it is fun to not know too. This interview has been edited and condensed.Layla Stahr is a Brevia staff writer. She can be reached at firstname.lastname@example.org.