Learning of Glycan Motifs Using Genetic Programming and Various Fitness Functions | Zendy

Tetsuhiro Miyahara | Zendy; Tetsuji Kuboyama | Zendy

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Learning of Glycan Motifs Using Genetic Programming and Various Fitness Functions

Author(s) -

Tetsuhiro Miyahara,

Tetsuji Kuboyama

Publication year - 2014

Publication title -

journal of advanced computational intelligence and intelligent informatics

Language(s) - English

Resource type - Journals

eISSN - 1343-0130

pISSN - 1883-8014

DOI - 10.20965/jaciii.2014.p0401

Subject(s) - glycan , genetic programming , computer science , tree (set theory) , fitness function , artificial intelligence , machine learning , genetic algorithm , biology , mathematics , genetics , mathematical analysis , glycoprotein

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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