Using data mining to identify structural rules in proteins

The progress in bioinformatics and biotechnology area has generated a huge amount of sequences that requires a detailed analysis. There are several data mining techniques that can be used to discovery patterns in large databases. This paper describes the development of a tool/methodology to extract hydrophobicity patterns/profiles that archives a specific secondary structure in proteins. The results indicate that association rules can be efficient method to investigate this kind of problem. This work contributes for two areas: prediction of protein structure and protein folding.