Using pseudo amino acid composition to predict protein subcellular location: approached with amino acid composition distribution

Amino Acids
J-Y ShiG-P Zhou

Abstract

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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Citations

Apr 23, 2008·Amino Acids·Xing-Ming ZhaoKazuyuki Aihara
Apr 19, 2008·Amino Acids·Zhi-Ping LiuLuonan Chen
Mar 22, 2014·International Journal of Molecular Sciences·Yue-Nong FanKuo-Chen Chou
Dec 6, 2011·Biochemical and Biophysical Research Communications·Qing-Bin GaoJia He
Dec 21, 2010·Journal of Theoretical Biology·Kuo-Chen Chou
Mar 24, 2010·Journal of Theoretical Biology·Loris NanniAlessandra Lumini
Feb 12, 2009·Journal of Clinical Monitoring and Computing·Shaomin Yan, Guang Wu
Nov 30, 2019·Current Pharmaceutical Design·Kuo-Chen Chou
Oct 17, 2019·Journal of Bioinformatics and Computational Biology·Fang YuanXueren Wang
Oct 7, 2018·Journal of Mathematical Biology·Li GeMatthias Dehmer

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