A novel representation for apoptosis protein subcellular localization prediction using support vector machine |
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Authors: | Li Zhang Dachao Li |
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Institution: | a School of Computer and Communication, Hunan University, Changsha Hunan 410082, China b School of Mathematics and Statistics, Hainan Normal University, Haikou Hainan 571158, China |
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Abstract: | Apoptosis, or programmed cell death, plays an important role in development of an organism. Obtaining information on subcellular location of apoptosis proteins is very helpful to understand the apoptosis mechanism. In this paper, based on the concept that the position distribution information of amino acids is closely related with the structure and function of proteins, we introduce the concept of distance frequency Matsuda, S., Vert, J.P., Ueda, N., Toh, H., Akutsu, T., 2005. A novel representation of protein sequences for prediction of subcellular location using support vector machines. Protein Sci. 14, 2804-2813] and propose a novel way to calculate distance frequencies. In order to calculate the local features, each protein sequence is separated into p parts with the same length in our paper. Then we use the novel representation of protein sequences and adopt support vector machine to predict subcellular location. The overall prediction accuracy is significantly improved by jackknife test. |
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Keywords: | Apoptosis protein Subcellular location Distance frequency Local features Support vector machine |
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