Next Wave: How did you get involved in this type of research?
Lila Kari: My background is in mathematics and computer science. The reason I got involved in biocomputation is that my colleague, Tom Head from the State University of New York, Binghamton, had developed a mathematical model for DNA recombination operations already in 1987. I was familiar with this model, [which is] very interesting from a theoretical point of view, but did not become actively involved until Gheorghe Paun brought to my attention the 1994 Science article by Len Adleman. This paper reported the results of an experiment that solved a computational problem, the Hamiltonian Path Problem, solely by manipulating DNA strands in test tubes. An astonishing scientific breakthrough, this made the connection between biology and computation much more real, and we became interested in studying the computational power of DNA-based computing. Together with Gheorghe Paun (and Rudi Freund) and extending some of his previous results, we proved that a model of DNA-based computing based on splicing had universal computational power.
I found this had fascinating implications because it meant that, in principle, moving and shaking DNA strands and enzymes in test tubes could carry out any problem that could be solved by an electronic computer. This also opened up interesting philosophical interpretations: Maybe in the same way physics and other sciences have been proved to have mathematical foundations, so biology and life itself might be ultimately governed by mathematical laws.
In some sense, we could think of this research connecting biology with computation and mathematics as the revenge of Plato. He intuited already 2500 years ago that behind the material things lie concepts, ideas, which are mathematically based. It is now up to us to scientifically prove that he was right, and research in biomolecular computing is a first step in this direction.
Next Wave: How does your work in biocomputing relate to nanobiotechnology?
Lila Kari: Some of the results I obtained with Laura F. Landweber on the computational power of gene rearrangement in ciliates indicate that, in principle, these unicellular organisms may have the capacity to perform at least any computation carried out by an ordinary computer. This opens the possibility of envisaging a programmable cell that could be used for a variety of computational and medical purposes.
Our research complements the ongoing work in gene circuits and engineering of intercellular communication that offer possible applications to medicine, agriculture, environmental monitoring, molecular scale manufacturing, and molecular electronics.
Next Wave: What do you perceive to be the needs of the nanobiotechnology discipline in terms of incoming researchers?
Lila Kari: There is a growing need for people who have strong backgrounds in both computer science and biochemistry. Canadians have great opportunities in this field as Canada has excellent training programs in computer science, mathematics, and biochemistry.
Next Wave: Where do you think the discipline is going, both scientifically and as an avenue of employment?
Lila Kari: There are many opportunities, both scientifically and job-wise. Scientifically, as always when two previously unconnected disciplines come together, there is a tremendous range of new questions begging to be solved. For a researcher who might have become bored or jaded if only embedded in his/her own discipline, finding another discipline that poses entirely different challenges and where his/her contributions can really make a difference is exhilarating. Being exposed to the problems of another discipline is the equivalent of finding a gold mine, and the gold rush now is for all these glittering, previously hidden molecular biology questions to be tackled and solved.
Dr. Lila Kari is an associate professor in the department of computer science at the University of Western Ontario. She received her Ph.D. in mathematics and computer science from the University of Turku, Finland, in 1991. Her current research interests include biomolecular computation, biological computation, and bioinformatics.
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