Learning of Glycan Motifs Using Genetic Programming and Various Fitness Functions
Tetsuhiro Miyahara* and Tetsuji Kuboyama**
*Graduate School of Information Sciences, Hiroshima City University, 3-4-1 Ozuka-higashi, Asaminami-ku, Hiroshima 731-3194, Japan
**Computer Centre, Gakushuin University, 1-7-1 Mejiro, Toshima-ku, Tokyo 151-8588, Japan
We apply a genetic programming approach to learning of glycan motifs by using tag tree patterns and various fitness functions. Tag tree patterns obtained from some glycan data show characteristic tree structures. We examine the effects of using various fitness functions on GP processes and obtained glycan motifs. We also show that our method is applicable to tree structured data other than glycan data.
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