Comparing Genomes

s new ways of using biological material to solve difficult computational problems continue to emerge, several fundamental questions arise: Are these techniques practical? If so, what are the key appli-cations? Do the techniques scale to larger prob-lems? Do they give us anything more than a few elegant theoretical insights into the nature of com-putation? Ultimately, is this a productive endeavor? Before exploring these questions, it might be fruitful to examine a quotation by Richard Feyn-mann, as it reflects on similar questions in the context of quantum-mechanical computers: The discovery of computers and the thinking about computers has turned out to be extremely useful in many branches of human reasoning. For instance, we never really understood how lousy our understanding of language was, the theory of grammar and all that stuff, until we tried to make a computer which would be able to understand language. We tried to learn a great deal about psychology by trying to understand how computers work. There are interesting philosophical questions about reasoning and relationship, observation , and measurement and so on, which computers have stimulated us to think about anew, with new types of thinking. And all I was doing was hoping that the computer type of thinking would give us some new ideas, if any are really needed. 2 In a similar vein, I argue that although bio-computing approaches use classical biotechnological tools, ultimately the reasoning and design style emerging in the biocomputing field will lead to more sophisticated, robust, and high-throughput biotechnology—a technology primarily centered around manipulating biological material in living cells (in vivo), in test tubes (in vitro), or in computational models (in silico) with the hope of creating a detailed picture of how living organisms function. To develop these ideas, this article focuses on just one example: using a randomized technique from the world of computer algorithms to compare two related genomes. This method of genome comparison, which has many applications in cancer research, was originally developed in collaboration with my colleague Mike Wigler and his laboratory at Cold Spring Harbor. The description here, focusing simply on the problem's computational aspect, uses some ideas from a recent article. Can it then be that there is…something of use for unraveling the universe to be learned from the philosophy of computer design?—J.A. Wheeler 1 The theory behind biocomputing is to look to biological structures and processes for new ways of solving difficult computational …