Application of neural networks to biological data mining: a case study in protein sequence classification

Jason Tsong-Li Wang, Qicheng Ma, Dennis E. Shasha, Cathy H. Wu

Abstract: Biological data mining aims to extract signi cant information from DNA, RNA and proteins. The signi cant information may refer to motifs, functional sites, clustering and classi cation rules. This paper presents an example of biological data mining: the classi cation of protein sequences using neural netw orks. We proposenew tec hniques to extract features from protein data and use them in combination with the Ba yesianneural network to classify protein sequences obtained from the PIR protein database maintained at the National Biomedical Research Foundation. T o evaluate the performance of the proposed approach, we compare it with other protein classi ers built based on sequence alignment and machine learning methods. Experimental results sho w the high precision of the proposed classi er and the complementarity of the tools studied in the paper.