Abstract
Biology and computer science share a natural affinity. Physicist Erwin Schrodinger envisioned life as an aperiodic crystal, observing that the organizing structure of life is neither completely regular, like a pure crystal, nor completely chaotic and without structure, like dust in the wind. Perhaps this is why biological information has never satisfactorily yielded to classical mathematical analysis. Machine computations combine elegant algorithms with brute-force calculations, which seems a reasonable approach to this aperiodic structure. Likewise, computing seeks to create a machine that can flexibly solve diverse problems. In nature, such plastic problem solving resides uniquely in the domain of organic matter. Thus, examining how organisms solve problems can lead to new computation and algorithm development approaches that devour the problems that are so easy to approach using a computer, yet so difficult to tackle in the laboratory. The paper discusses the two most successful uses of computers in biology, comparative sequence analysis and in silico cloning. It considers DNA computing and genetic algorithms.
Published Version
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