Using computer science to better understand biology
Many of the students in Associate Professor of Biology Steve Freedberg’s bioinformatics course aren’t computer science majors. Many have little experience writing code.
Yet all of them have developed computer programs that provide a sophisticated research tool for understanding biological systems.
As part of the course, many of the students use simulations to describe genetic processes, but others have used them to study population biology and evolution as well.
Freedberg began using computer simulation modeling to teach population evolution several semesters ago. The programs work by running a series of loops representing population situations.
As students continue to build off the coding done in previous semesters, their programs have begun to reach surprising levels of sophistication and usefulness.
“The students are impressively autonomous on these programs,” says Freedberg. While he guides their research questions and helps them interpret their results, the students have to be creative in their writing of programs.
Elaine Rood ’15, for example, worked with Freedberg through the college’s Collaborative Undergraduate Research and Inquiry (CURI) program to develop a computer program that starts with two populations of a species that are identical except for their sex ratio. The program loops through these populations’ many lifecycles until one of the populations goes extinct. The results illustrate how the sex ratio of a population affects its competitive ability.
Her program might, for instance, start with one population of butterflies that has more females than males, while the other has an equal sex ratio. She would simulate these butterflies living for many generations until one of the populations goes extinct — a sort of survival of the fittest.
“It’s exciting when you’ve been debugging for a long time and your code finally works like it’s supposed to. Then you actually get to see your results, which can be really interesting,” Rood says.
The simulations can be made less hypothetical by including real genetic and ecological parameters. “The results of these simulations may shed light on processes that would be impossible to study in living populations,” says Freedberg.
The evolution of these programs occurs not only through Freedberg’s courses, but also through individual student research opportunities.
Under Freedberg’s advisement, Spencer Debenport ‘10 took the backbone of a model that examined sex ratio theory and incorporated genetics into it. Incorporating genetics the program “allows us to make important insights into how sex determining systems evolve,” says Freedberg. Debenport and Freedberg’s research was published in the Journal of Evolutionary Biology earlier this year.
Most recently, Rood repurposed the model from Debenport and began studying systems characterized by uniparental sex ratio distortion, a widespread phenomenon potentially associated with the success of some invasive species.
Freedberg says that in the future he hopes to write a grant proposal to fund student research centered around this program. He also hopes to integrate computer simulation modeling as a study system that will allow students to work on a range of questions that couldn’t be addressed with living organisms.
“This type of freedom can really get students excited about biology because their methodology is only constrained by their imagination,” says Freedberg.