Prediction of subcellular location apoptosis proteins with ensemble classifier and feature selection |
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Authors: | Quan Gu Yong-Sheng Ding Xiao-Ying Jiang Tong-Liang Zhang |
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Institution: | (1) College of Information Sciences and Technology, Donghua University, 201620 Shanghai, China;(2) Engineering Research Center of Digitized Textile & Fashion Technology, Ministry of Education, 201620 Shanghai, China;(3) School of Chemistry and Chemical Engineering, Henan Institute of Science and Technology, Xinxiang, 453003 Henan, China;(4) Research Institute of Highway, Research Institute of Highway Ministry of Communications, 100088 Beijing, China; |
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Abstract: | Apoptosis proteins have a central role in the development and the homeostasis of an organism. These proteins are very important
for understanding the mechanism of programmed cell death. The function of an apoptosis protein is closely related to its subcellular
location. It is crucial to develop powerful tools to predict apoptosis protein locations for rapidly increasing gap between
the number of known structural proteins and the number of known sequences in protein databank. In this study, amino acids
pair compositions with different spaces are used to construct feature sets for representing sample of protein feature selection
approach based on binary particle swarm optimization, which is applied to extract effective feature. Ensemble classifier is
used as prediction engine, of which the basic classifier is the fuzzy K-nearest neighbor. Each basic classifier is trained
with different feature sets. Two datasets often used in prior works are selected to validate the performance of proposed approach.
The results obtained by jackknife test are quite encouraging, indicating that the proposed method might become a potentially
useful tool for subcellular location of apoptosis protein, or at least can play a complimentary role to the existing methods
in the relevant areas. The supplement information and software written in Matlab are available by contacting the corresponding
author. |
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Keywords: | |
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