A new approach to the prediction of eukaryotic PolII promoters from DNA sequence takes advantage of a combination of elements similar to neural networks and genetic algorithms to recognize a set of discrete subpatterns with variable separation as one pattern: a promoter. The neural networks use as input a small window of DNA sequence, as well as the output of other neural networks. Through the use of genetic algorithms, the weights in the neural networks are optimized to discriminate maximally between promoters and non-promoters.