Manolis Kamvysselis: Pursuing New Challenges
By Karen Hopkin

When Manolis Kamvysselis was 12 years old, he and his family moved from Athens to a small town in southern France. "My dad just woke up one morning and said, 'Let's go.'" His father, who grew up in a village in Greece, wanted his children to be bilingual—a skill he regretted never having gained himself. So they hit the road. "We didn't ask questions. We just went," says Kamvysselis, who is now a graduate student working with Eric Lander at the Whitehead Institute/MIT Center for Genome Research. "Four months later, we were living in France."

The move changed Kamvysselis's life. "In a new language and new environment I had to work really hard," he says. "And I learned that working hard is normal."

It also gave him a unique and intimate appreciation of mathematics. "Learning a new language, I was able to step back and realize that words are just placeholders for meanings. They're abstractions." And the same is true in math—a discipline that is all about abstraction. "Terms like x and y have no meaning on their own," notes Kamvysselis. "They are placeholders for other information."

Four years after the move to France, Kamvysselis was one of the top 100 students in the country. "People said, 'Oh, he's good at math because he's Greek,'" Kamvysselis laughs. "But really it was because I had to overcome the language barrier."

Although Kamvysselis loved math, he yearned to find a practical application for his skills. So, after having learned English as a foreign language in high school, he enrolled as a computer science major at the Massachusetts Institute of Technology. There he learned to use computers to tackle a variety of problems: solving geometric surfaces in multiple dimensions, building models for human motion, and programming robots to cooperate by following simple rules, like ants in a colony. "I worked on a different problem every six months," says Kamvysselis. Taking on diverse tasks taught him how to absorb knowledge, adapt quickly to new situations, and use his talents to do something novel.

That was excellent training for the work Kamvysselis now does with Lander, where he applies his skills as computer scientist and mathematician to learn something new about how cells work. "From an engineer's perspective, looking at life and how life works really makes sense," he says. After all, a cell is like a robot that evolution has designed and assembled. The information encoded in its DNA is like the program that runs the machine. And Kamvysselis is working on cracking the code that cells use to live—and to evolve.

Working with Lander and his colleagues at the Whitehead Institute, Kamvysselis is comparing the genome sequences of four different species of Saccharomyces, a budding yeast that bakers and brewers have used in bread and beer for centuries. Using computer programs that he wrote himself, Kamvysselis is searching these yeast genomes for patterns. He is specifically looking for short signals that are distributed nonrandomly throughout the DNA. Sequences that are biologically important to the survival of an organism, the researchers theorize, will be conserved by evolution. They will look the same and crop up in the same places in the genomes of different organisms—in this case, closely related species of yeast.

So far the data look good. Kamvysselis and company are finding patterns and identifying elements that appear again and again throughout the yeast genomes. Now the researchers are working on correlating these signals with their functions to understand how they regulate gene expression and enable genes to work together to build and operate a machine as dynamic as a living cell.

To tease patterns from these genomes, Kamvysselis has written thousands of lines of computer code. His days are a continuous loop of looking at data, writing programs for probing the data, and testing new ideas. "Work, observe, work, observe, work, observe," as Kamvysselis puts it.

Much of his work is actually done at home, where Kamvysselis shuffles from bed to computer and back again—with occasional trips to the refrigerator. "The danger of working independently at home is that you'll make more trips to the fridge than you'll write lines of code," he says. Of course it also has its advantages. "You can sleep late if you worked too hard or partied too hard the night before," says Kamvysselis. "Or you can go to the beach if it's sunny on a Thursday but rainy on Saturday." But then, it's back to work—which is fine with Kamvysselis. "Doing a Ph.D. takes a lot of self-motivation and you have to love what you do," he explains. "But I love what I do. It's like I'm a kid still playing with toys. They're just different toys."

Kamvysselis is finishing his second year of graduate school, and if all goes well he hopes to graduate in a year or so. As for the future, Kamvysselis is still undecided. He might want to teach, or do postdoctoral work, or maybe go out and do something totally new. Until then, he will certainly continue to work hard—and play hard, too. When he's not in the lab, Kamvysselis enjoys getting physical: biking, in-line skating, or salsa dancing. "Being stuck in a chair all the time, my hobbies involve getting out and working my body," he says. "It's important to try to find some balance. I'm not just a brain."

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