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Genomics Inform > Volume 2(3); 2004 > Article
Application of Decision Tree for the Classification of Antimicrobial Peptide.
Su Yeon Lee, Sunkyu Kim, Sukwon S Kim, Seon Jeong Cha, Young Keun Kwon, Byung Ro Moon, Byeong Jae Lee
1Interdisciplinary Program in Bioinformatics, Seoul National University, Seoul 151-742, Korea.
2Laboratory of Molecular Genetics, School of Biological Sciences, Institute of Molecular Biology and Genetics, Seoul National University, Seoul 151-742, Korea.
3Optimization Laboratory, School of Computer Science and Engineering, Seoul National University, Seoul 151-742, Korea.
Abstract
The purpose of this study was to investigate the use of decision tree for the classification of antimicrobial peptides. The classification was based on the activities of known antimicrobial peptides against common microbes including Escherichia coli and Staphylococcus aureus. A feature selection was employed to select an effective subset of features from available attribute sets.Sequential applications of decision tree with 17 nodes with 9 leaves and 13 nodes with 7 leaves provided the classification rates of 76.74% and 74.66% against E. coli and S. aureus, respectively. Angle subtended by positively charged face and the positive charge commonly gave higher accuracies in both E. coli and S. aureus datasets. In this study, we describe a successful application of decision tree that provides the understanding of the effects of physicochemical characteristics of peptides on bacterial membrane.
Keywords: decision tree; classification; antimicrobial peptides
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