Artificial evolution has emerged as a powerful computationalstrategy for solving complex problems in the biologicaland biomedical sciences. Inspired by biological evolution,artificial evolution is attractive because it employs stochasticsearch algorithms that are inherently parallel. As such, thesenovel approaches are ideal for biological and biomedi-cal problems that are high-dimensional, noisy, and verycomplex. The papers that appear in this special issue ofthe Journal of Artificial Evolution and Applications wererigorously peer reviewed and represent a wide range ofdifferent algorithms and application areas. As such, thepapers in this special issue represent both the depth andbreadth of artificial evolution and its potential applications.Papers in this volume cover a range of artificial evolutionalgorithms including, for example, genetic algorithms andgenetic programming. Application areas span multiple dif-ferent areas including the classification of microarray data,classification and diagnosis of cancer, multiple sequencealignment, ecological simulation, population genetics, andneurological discrimination.
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