Abstract
We propose a neural network method for three dimensional protein structure search that utilizes the link relationships among features. This method is an offline index-based method which builds indices for protein structures in the database and the search is performed on the indices. We can easily extend this method to incoporate more physical properties of the protein structures since the structural information is preserved in the extracted features.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Brown, N.P., Orengo, C.A., Taylor, W.R.: A protein structure comparison methodology. Computational Chemistry 20, 359–380 (1996)
Caianiel, E.R., Capocelli, R.M.: On form and language: The procrustes algorithm for feature extraction. Biological Cybernetics 8, 223–233 (1971)
Gao, F., Zaki, M.J.: Psist: Indexing protein structures using suffix trees. In: Proceedings of IEEE Computational Systems Bioinformatics Conference (CSB), pp. 212–222 (2005)
Godzik, A., Skolnick, J.: Flexible algorithm for direct multiple alignment of protein structures and sequences. Computer Applications in the Biosciences 10(6), 587–596 (1994)
Holm, L., Sander, C.: Protein structure comparison by alignment of distance matrices. Journal of Molecular Biology 233, 123–138 (1993)
Hopfield, J.J., Tank, D.W.: Neural computation of decisions in optimization problems. Biological Cybernetics 52, 141–152 (1985)
Kabsch, W.: A solution for the best rotation to relate two sets of vectors. Acta Crystallographica A32, 922–923 (1978)
Liou, C.-Y.: Backbone structure of hairy memory. In: Kollias, S., Stafylopatis, A., Duch, W., Oja, E. (eds.) ICANN 2006. LNCS, vol. 4132, pp. 688–697. Springer, Heidelberg (2006)
Liou, C.-Y., Lin, S.-L.: Finite memory loading in hairy neurons. Natural Computing 5(1), 15–42 (2006)
Liou, C.-Y., Yang, H.-C.: Handprinted character recognition based on spatial topology distance measurement. IEEE Transactions on Pattern Analysis and Machine Intelligence 18(9), 941–945 (1996)
Liou, C.-Y., Yang, H.-C.: Selective feature-to-feature adhesion for recognition of cursive handprinted characters. IEEE Transactions on Pattern Analysis and Machine Intelligence 21(2), 184–191 (1999)
Liou, C.-Y., Yang, H.-C.: Self-organization of high-order receptive fields in recognition of handprinted characters. In: ICONIP, Perth, Australia, November 1999, pp. 1161–1166 (1999)
Aiyer, M.N.S.V.B., Fallside, F.: A theoretical investigation into the performance of the hopfield model. IEEE Transactions on Neural Networks 1(2), 204–215 (1990)
Shibuya, T.: Geometric suffix tree: A new index structure for protein 3-d structures. In: Lewenstein, M., Valiente, G. (eds.) CPM 2006. LNCS, vol. 4009, pp. 84–93. Springer, Heidelberg (2006)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2008 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Liou, CY., Ho, CJ. (2008). Neural Network Method for Protein Structure Search Using Cell-Cell Adhesion. In: Ishikawa, M., Doya, K., Miyamoto, H., Yamakawa, T. (eds) Neural Information Processing. ICONIP 2007. Lecture Notes in Computer Science, vol 4985. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-69162-4_36
Download citation
DOI: https://doi.org/10.1007/978-3-540-69162-4_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-69159-4
Online ISBN: 978-3-540-69162-4
eBook Packages: Computer ScienceComputer Science (R0)