Building a Knowledge-Base for Protein Function Prediction using Multistrategy Learning

Conventional techniques for protein function prediction using similarities of amino acid sequences enable us to only classify the protein functions into function groups. They usually fail to predict speci c protein functions. To overcome the limitation, in this paper, we propose a method for protein function prediction using functional feature analysis and a multistrategy learning approach to building the knowledge-base. By \functional feature", we mean a feature of an amino acid sequence characterizing the function of a protein with the amino acid sequence. They are secondary and/or tertiary structures of amino acid sequences that corresponds to functional elements comprising the functions of a protein. The functional features are extracted from amino acid sequences using Abductive inference, Inductive inference, and Deductive inference. In this paper, we show the e ectiveness of the method by an example problem to classify functions of bacteriorhodopsin-like proteins. 石川 孝:木更津工業高等専門学校 情報工学科,〒 292 千葉県木更津市清見台東 2-11-1 美宅成樹,広川貴次,諏訪牧子,謝 文清:東京農工大学工学部,〒 184 東京都小金井市中町 2-24-16 寺野隆雄:筑波大学社会工学系 経営システム科学,〒 112 東京都文京区大塚 3-29-1