Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino pairs

Bioinformatics

Volumn 19, Issue 13, 2003, Pages 1656-1663

  Park, Keun Joon ^a   Kanehisa, Minoru ^a  

^a KYOTO UNIVERSITY   (Japan)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID;

ACCURACY; ALGORITHM; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ANALYTIC METHOD; ARTICLE; BIOINFORMATICS; CELL MEMBRANE; CELL NUCLEUS; CELL VACUOLE; CHLOROPLAST; CONTROLLED STUDY; CYTOPLASM; CYTOSKELETON; DATA BASE; ENDOPLASMIC RETICULUM; EUKARYOTIC CELL; GENOME; GOLGI COMPLEX; INTERNET; LYSOSOME; MITOCHONDRION; NONHUMAN; PEROXISOME; PREDICTION; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN LOCALIZATION; SWISS-PROT;

EUKARYOTA;

EID: 0141515750     PISSN: 13674803     EISSN: None     Source Type: Journal    
DOI: 10.1093/bioinformatics/btg222     Document Type: Article

References (19)

1. Bairoch, A. and Apweiler, R. (2000) The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Res., 28, 45-48.
2. Brown, M.P.S., Grundy, W.N., Lin, D., Cristianini, N., Sugnet, C.W., Furey, T.S., Ares, M. and Haussler, D. (2000) Knowledge-based analysis of microarray gene expression data by using support vector machines. Proc. Natl Acad. Sci. USA, 97, 262-267.
3. Cai, Y.D., Liu, X.J., Xu, X.B. and Chou, K.C. (2002) Support vector machines for prediction of protein subcellular location by incorporating quasi-sequence-order effect. J. Cell Biochem., 84, 343-348.
4. Chou, K.C. (2000) Prediction of protein subcellular locations by incorporating quasi-sequence-order effect. Biochem. Biophys. Res. Commun., 278, 477-483.
5. Chou, K.C. (2001) Prediction of protein cellular attributes using pseudo-amino acid composition. Proteins, 43, 246-255.
6. Chou, K.C. and Elrod, D.W. (1999a) Protein subcellular location prediction. Protein Eng., 12, 107-118.
7. Chou, K.C. and Elrod, D.W. (1999b) Prediction of membrane protein types and subcellular locations, Proteins, 34, 137-153.
8. Cristianini, N. and Shawe-Taylor, J. (2000) An Introduction to Support Vector Machines and other Kernel-Based Learning Methods. Cambridge University Press, Cambridge, MA.
9. Ding, C. and Dubchak, I. (2001) Multi-class protein fold recognition using support vector machines and neural networks. Bioinformatics, 17, 349-358.
10. Emanuelsson, O., Nielsen, H., Brunak, S. and von Heijne, G. (2000) Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol., 300, 1005-1016.
11. Furey, T.S., Cristianini, N., Duffy, N., Bednarski, D.W., Schummer, M. and Haussler, D. (2000) Support vector machine classification and validation of cancer tissue samples using microarray expression data. Bioinformatics, 16, 906-914.
12. Hua, S. and Sun, Z. (2001a) Support vector machine approach for protein subcellular localization prediction. Bioinformatics, 17, 721-728.
13. Hua, S. and Sun, Z. (2001b) A novel method of protein secondary structure prediction with high segment overlap measure: support vector machine approach. J. Mol. Biol., 308, 397-407.
14. Joachims, T. (1999). In Schölkopf, B., Burges, C. and Smola, A. (ed.), Making Large-Scale SVM Learning Practical. Advances in Kernel Methods-Support Vector Learning. MIT Press, Cambridge MA.
15. Myers, E.W. and Miller, W. (1988) Optimal alignments in linear space. CABIOS, 4, 11-17.
16. Nakai, K. and Kanehisa, M. (1992) A knowledge base for predicting protein localization sites in eukaryotic cells. Genomics, 14, 897-911.
17. Nakai, K. (2000) Protein sorting signals and prediction of subcellular localization. Adv. Protein Chem., 54, 277-344.
18. Reinhardt, A. and Hubbard, T. (1998) Using neural networks for prediction of the subcellular location of proteins. Nucleic Acids Res., 26, 2230-2236.
19. Yuan, Z. (1999) Prediction of protein subcellular locations using Markov chain models. FEBS Lett., 451, 23-26.