Abstract
This paper investigates the use of the method of dimensional reduction Cascaded Nonlinear Components Analysis (C-NLPCA) in the protein secondary structure prediction problem. The use of the C-NLPCA is justified by the fact that this method manage to obtain a dimensional reduction that considers the nonlinearity of the data. In order to prove the effectiveness of the C-NLPCA, this paper presents comparisons of methods of components extraction, as well as, of existing predictors. The C-NLPCA revealed to be efficient, propelling a new field of research.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Altchul, S., Madden, T., Shaffer, A., Zhang, J., Zhang, Z., Miller, W., Lipman. D.: Gapped Blast and PSI-Blast: A New Generation of Protein Database Search Programs. Nucleic Acids Research (1997).
Botelho, S.S.C., Bem, R.A., Almeida, I.L., Mata, M.M.: C-NLPCA: Extracting Non-Linear Principal Components of Image Datasets. Simpósio Brasileiro de Sensoriamento Remoto (2005).
Cuff, A.J., Barton, J.G.: Evaluation and Improvement of Multiple Sequence Methods for Protein Secondary Structure Prediction. Proteins Structure, Function and Genetics, 34 (1999) 508–519.
Guimaraes, K.S., Melo, J.C.B., Cavalcanti, G.D.C.: Combining few Neural Networks for Effective Secondary Structure Prediction. Proceedings of the Third IEEE Symposion on Bioinformatics and Bioengineering (2003) 415–420.
Jones, D.T.: Protein Secondary Structure Prediction Based on Position-Specific Scoring Matrices. J. Mol. Biol. 292 (1999) 195–202.
Khattree, R., Naik, D.N.: Multivariate Data Reduction and Discrimination with SAS Software. Cary, NC: SAS Institute Inc. (2000).
King, R., Sternberg, M.: Identification and Application of the Concepts Important for Accurate and Reliable Protein Secondary Structure Prediction. Proteins Science 5 (1996) 2298–2310.
Kramer, M.A.: Nonlinear Principal Component Analysis Using Autoassociative Neural Networks. AlChe Jounal 37 (1991) 233–243.
Lehninger, A.L.: Principles of Biochemist. Editora Sarvier, São Paulo (1984).
Melo, J.C.B., Cavalcanti, G.D.C., Guimaraes, K.S.: PCA Feature Extraction for Protein Structure Prediction. International Joint Conference on Neural Networks (2003a) 2952–2957.
Melo, J.C.B., Cavalcanti, G.D.C., Guimaraes, K.S.: Protein Secondary Structure Prediction with ICA Feature Extraction. Proceedings of the IEEE International Workshop on Neural Networks for Signal Processing — Special Session on Bioinformatics (2003b).
Melo, J.C.B., Cavalcanti, G.D.C., Guimaraes, K.S.: Protein Secondary Structure Prediction: Efficient Neural Network and Feature Extraction. IEE Electronics Letters, Vol. 40, n. 21 (2004) 1358–1359.
Qian, N., Setnowski, T.J.: Predicting the Secondary Structure of Globular Proteins Using Neural Network Models. Baltimore (1988).
Rost, B., Sander, C.: Combining Evolutionary Information and Neural Network to Predict Secondary Structure. Proteins 19 (1994) 55–72.
Salamov, A., Solovyev. M.: Prediction of Protein Secondary Structure by Combining Ñearest-Neighbor Algorithm and Multiple Sequence Alignments. Journal of Molecular Biology 247 (1995) 11–15.
University of Dundee and The Barton Group. Cb396. http://www.compbio.dundee.ac.uk/, 20 jul 2005.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Simas, G.M., Botelho, S.S.C., Grando, N., Colares, R.G. (2007). Dimensional Reduction in the Protein Secondary Structure Prediction — Nonlinear Method Improvements. In: Corchado, E., Corchado, J.M., Abraham, A. (eds) Innovations in Hybrid Intelligent Systems. Advances in Soft Computing, vol 44. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74972-1_55
Download citation
DOI: https://doi.org/10.1007/978-3-540-74972-1_55
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74971-4
Online ISBN: 978-3-540-74972-1
eBook Packages: EngineeringEngineering (R0)