In this paper, an extraction and classification feature approach of biological sequences based on profiles built using an association analysis is proposed. The most important features of the approach are: i) The use of data mining techniques to perform knowledge extraction from biological sequences. Specifically an association analysis process is proposed as a methodology for discovering interesting relationships hidden in biological data sets; and ii) Some learning classifiers are proposed to be trained using binary profiles obtained from the association analysis process. These learning methods were applied over a sequence structure layer of secondary structure predictors to analyze the performance of association rules as a pattern extraction method. Some experiments were carried out to validate the proposed approach obtaining very promising results.