Using OWA operators for gene sequential pattern clustering

Nowadays, the management of sequential patterns data becomes an increasing need in biological knowledge discovery processes. An important task in these processes is the restitution of the results obtained by using data mining methods. In a complex domain as biomedical, an efficient interpretation of the patterns without any assistance is difficult. One of the most common knowledge discovery process is clustering. But the application of clustering to gene sequential patterns is far from easy on biomedical data. In this paper, we introduce a new gene sequential patterns similarity function and summarization algorithm.