Computer recognition of short functional sites on DNA, such as promoter regions or intron-exon boundaries, has recently attracted much interest. In this paper we have focused our attention on the automatic recognition of relevant features of human nucleic acid sequences by means of an unsupervised artificial neural network model. Sixty messenger RNA and 31 genomic DNA sequences were analysed. The results showed that in mRNA, the minimal similarity 60 base pattern was guanine- and cytosine-rich and located in most sequences in a range of 250 bases from either the middle point of the signal peptide coding region or from the start of the coding region. On DNA sequences a region defined by a cluster of minimal similarity patterns was present in many of the analysed genes. This zone may be related to alternative splicing and DNA methylation.