Abstract
Apoptosis proteins have a central role in the development and homeostasis of an organism. These proteins are very important for understanding the mechanism of programmed cell death, and their function is related to their types. According to the classification scheme by Zhou and Doctor (2003), the apoptosis proteins are categorized into the following four types: (1) cytoplasmic protein; (2) plasma membrane-bound protein; (3) mitochondrial inner and outer proteins; (4) other proteins. A powerful learning machine, the Support Vector Machine, is applied for predicting the type of a given apoptosis protein by incorporating the sqrt-amino acid composition effect. High success rates were obtained by the re-substitute test (98/98 = 100 %) and the jackknife test (89/98 = 90.8%).
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References
Barinaga, M. (1998). Stroke-damaged neurons may commit cellular suicide. Science 281: 1302–1303.
Cai, Y.D. and K.C. Chou (2003). Nearest neighbour algorithm for predicting protein subcellular location by combing functional domain composition and pseudo-amino acid composition. Biochemical and Biophysical Research Communications 305: 407–411.
Cai, Y.D., G.P. Zhou and K.C. Chou (2003). Support vector machine for predicting membrane protein types by using functional domine composition. Biophysical Journal 84: 3257–3263.
Cai, Y.D., X.J. Liu and K.C. Chou (2001). Artificial neural network model for predicting membrane protein types. Journal of Biomolecular Stereodynamics 18: 607–610.
Cai, Y.D., X.J. Liu, X.B. Xu and K.C. Chou (2000a). Support vector machines for prediction of protein subcellular location. Molecular Cell Biology Research Communications 4: 230–233.
Cai, Y.D., X.J. Liu, X.B. Xu and K.C. Chou (2000b). Support vector machines for prediction of protein subcellular location by incorporating quasi-sequence-order effect. Journal of Biological Chemistry 84: 343–348.
Chou, J.J., H. Li, G.S. Salvesen, J. Yuan and G. Wagner (1999). Solution structure of BID, an intracellular amplifier of apoptotic signaling. Cell 96: 615–624.
Chou, K.C. (1995). A novel approach to predicting protein structural classes in a (20-1)-D amino acid composition space. Proteins: Structure, Function and Genetics 21: 319–344.
Chou, K.C. (1999). A key driving force in determination of protein structural classes. Biochemical and Biophysical Research Communications 264: 216–224.
Chou, K.C. (2000a). Prediction of protein subcellular locations by incorporation quasi-sequence-order effect. Bichemical and Biophysical Research Communication 19: 477–483.
Chou, K.C. (2000b). Review: Prediction of protein structural classes and subcellular location. Current Protein and Peptide Science 1: 171–208.
Chou, K.C. (2001). Prediction of protein cellular attributes using pseudo-amino-acid-composition. Proteins: Structure, Function, and Genetics 43: 246–255.
Chou, K.C. and Y.D. Cai (2002). Using functional domain composition and support vector machines for prediction of protein subcellular location. Journal of Biology Chemistry 277: 45765–45769.
Chou, K.C. and Y.D. Cai (2003a). A new hybrid approach to predict subcellular localization of proteins by incorporating Gene ontology. Bichemical and Biophysical Research Communication 311: 743–747.
Chou, K.C. and Y.D. Cai (2003b). Predication and classification of protein subcellular location:sequence-order effect and pseudo amino composition. Journal of Cellular Biochemistry 90: 1250–1260.
Chou, K.C. and D.W. Elrod (1999a). Prediction of membrane protein types and subcellular locations. Proteins 34: 137–153.
Chou, K.C. and D.W. Elrod (1999b). Protein subcellular location prediction. Protein Engineering 12: 107–118.
Chou, K.C., D. Jones and R.L. Heinrikson (1997). Prediction of the tertiary structure and substrate binding site of caspase-8. FEBS Letters 419: 49–54.
Chou, K.C. and G.M. Maggiora (1998). Domain structural class prediction. Protein Engineering 11: 523–538.
Chou, K.C., A.G. Tomasselli and R.L. Heinrikson (2000). Prediction of the tertiary structure of a caspase-9/inhibitor complex. FEBS Letters 470: 249–256.
Chou, K.C. and C.T. Zhang (1994). Review: Predicting protein folding types by distance functions that make allowances for amino acid interactions. Journal of Biological Chemistry 269: 22014–22020.
Chou, K.C. and C.T. Zhang (1995). Prediction of protein structural classes. Critical Reviews in Biochemistry and Molecular Biology 30: 275–349.
Cortes, C. and V. Vapnik (1995). Support vector networks. Machine Learning 20: 273–293.
Ding, C.H. and I. Dubchak (2001). Multi-class protein fold recognition using support vector machines and neural networks. Bioinformatics 17: 349–358.
Evan, G. and T. Littlewood (1998). A matter of life and cell death. Science 281: 1317–1322.
Feng, Z.P. (2001). Prediction of the subcellular location of prokaryotic proteins based on a new representation of the amino acid composition. Biopolymers 58: 491–499.
Hua, S.J. and Z.R. Sun (2001a). Support vector machine approach for protein subcellular localization prediction. Bioinformatics 17: 721–728.
Hua, S.J. and Z.R. Sun (2001b). A novel method of protein secondary structure prediction with high segment overlap measure: Support vector machine approach. Journal of Molecular Biology 308: 397–407.
Jacobson, M.D., M. Weil and M.C. Raff (1997). Programmed cell death in animal development. Cell 88: 347–354.
Kerr, J.F., A.H. Wyllie and A.R. Currie (1972). Apoptosis: A basic biological phenomenon with wide-ranging implications in tissue kinetics. British Journal of Cancer 26: 239–257.
Pan, Y.X., Z.Z. Zhang, Z.M. Guo, G.Y. Feng, Z.D. Huang and L. He (2003). Application of pseudo amino acid composition for predicting protein subcellular location: Stochastic signal processing approach. Journal of Protein Chemistry 22: 395–402.
Reed, J.C. and G. Paternostro (1999). Postmitochondrial regulation of apoptosis during heart failure. Proceedings of the National Academy of Sciences 96: 7614–7616.
Schulz, J.B., M. Weller and M.A. Moskowitz (1999). Caspases as treatment targets in stroke and neurodegenerative diseases. Annals of Neurology 45: 421–429.
Suzuki, M., R.J. Youle and N. Tjandra (2000). Structure of Bax: Coregulation of dimer formation and intracellular location. Cell 103: 645–654.
Vapnik, V. (1998). Statistical Learning Theory. Wiley Interscience, New York.
Zhang, S.W., Q. Pan, H.C. Zhang, Y.L. Zhang and H.Y. Wang (2003). Classification of protein quaternary structure with support vector machine, Bioinformatics 19: 2390–2396.
Zhao, Y.D., C. Pinilla, D. Valmori, R. Martin and R. Simon (2003). Application of support vector machines for T-cell epitopes prediction, Bioinformatics 19: 1978–1984.
Zhou, G.P. (1998). An intriguing controversy over protein structural class prediction. Journal of Protein Chemistry 17: 729–738.
Zhou, G.P. and N. Assa-Munt (2001). Some insights into protein structural class prediction. Proteins: Structure, Function, and Genetics 44: 57–59.
Zhou, G.P. and K. Doctor (2003). Subcelluar location of Apoptosis proteins. Proteins: Structure, Function, and Genetic 50: 44–48.
Zhou, P., J. Chou, R.S. Olea, J. Yuan and G. Wagner (1999). Solution structure of Apaf-1 CARD and its interaction with caspase-9 CARD: A structural basis for specific adaptor/caspase interaction. Proceedings of the National Academy of Sciences 96: 11265–11270.
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Huang, J., Shi, F. Support Vector Machines for Predicting Apoptosis Proteins Types. Acta Biotheor 53, 39–47 (2005). https://doi.org/10.1007/s10441-005-7002-5
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DOI: https://doi.org/10.1007/s10441-005-7002-5