期刊
AMINO ACIDS
卷 35, 期 2, 页码 321-327出版社
SPRINGER WIEN
DOI: 10.1007/s00726-007-0623-z
关键词
protein subcellular localization; amino acid composition distribution; pseudo amino acid composition; support vector machines
In the Post Genome Age, there is an urgent need to develop the reliable and effective computational methods to predict the subcellular localization for the explosion of newly found proteins. Here, a novel method of pseudo amino acid (PseAA) composition, the so-called amino acid composition distribution (AACD), is introduced. First, a protein sequence is divided equally into multiple segments. Then, amino acid composition of each segment is calculated in series. After that, each protein sequence can be represented by a feature vector. Finally, the feature vectors of all sequences thus obtained are further input into the multi-class support vector machines to predict the subcellular localization. The results show that AACD is quite effective in representing protein sequences for the purpose of predicting protein subcellular localization.
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