HAKKE: A Multi-Strategy Prediction System for Sequences

We developed a machine learning system HAKKE which is suitable for predicting functional regions from sequences, such as protein-coding region prediction, and transmembrane domain prediction. HAKKE is a hybrid system cooperated by a number of algorithms of a pool to make an accurate prediction. The system uses an extension of the weighted majority algorithm in order to t the strength of each algorithm into given training examples. In this paper, we describe the core of the system and show some experimental results on transmembrane domain and -helix predictions.

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