Predicting subcellular location of apoptosis proteins with pseudo amino acid composition: approach from amino acid substitution matrix and auto covariance transformation |
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Authors: | Xiaoqing Yu Xiaoqi Zheng Taigang Liu Yongchao Dou Jun Wang |
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Institution: | (1) Department of Mathematics, Shanghai Normal University, 200234 Shanghai, China;(2) Scientific Computing Key Laboratory of Shanghai Universities, 200234 Shanghai, China;(3) College of Information Sciences and Engineering, Shandong Agricultural University, 271018 Taian, China;(4) School of Mathematical Sciences, Dalian University of Technology, 116024 Dalian, China; |
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Abstract: | Apoptosis proteins are very important for understanding the mechanism of programmed cell death. Obtaining information on subcellular
location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on amino acid substitution
matrix and auto covariance transformation, we introduce a new sequence-based model, which not only quantitatively describes
the differences between amino acids, but also partially incorporates the sequence-order information. This method is applied
to predict the apoptosis proteins’ subcellular location of two widely used datasets by the support vector machine classifier.
The results obtained by jackknife test are quite promising, indicating that the proposed method might serve as a potential
and efficient prediction model for apoptosis protein subcellular location prediction. |
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