Banzhaf Wolfgang, Beslon Guillaume, Christensen Steffen, Foster James A, Képès François, Lefort Virginie, Miller Julian F, Radman Miroslav, Ramsden Jeremy J
Department of Computer Science, Memorial University of Newfoundland, St John's, Newfoundland and Labrador A1B 3X5, Canada.
Nat Rev Genet. 2006 Sep;7(9):729-35. doi: 10.1038/nrg1921. Epub 2006 Aug 8.
Computational scientists have developed algorithms inspired by natural evolution for at least 50 years. These algorithms solve optimization and design problems by building solutions that are 'more fit' relative to desired properties. However, the basic assumptions of this approach are outdated. We propose a research programme to develop a new field: computational evolution. This approach will produce algorithms that are based on current understanding of molecular and evolutionary biology and could solve previously unimaginable or intractable computational and biological problems.
至少50年来,计算科学家们一直在开发受自然进化启发的算法。这些算法通过构建相对于所需属性“更合适”的解决方案来解决优化和设计问题。然而,这种方法的基本假设已经过时。我们提出了一个研究计划,以发展一个新领域:计算进化。这种方法将产生基于当前对分子和进化生物学理解的算法,并能够解决以前无法想象或棘手的计算和生物学问题。