Abstract
In this paper, we present a new hypersphere machine learning method and use it to predict all protein secondary structures. It finds sequences with sufficiently high homology. Prediction accuracy of the new method with protein secondary structures was good (average 89.3%). However, the method could not classify all test cases.
This is a preview of subscription content, log in via an institution to check access.
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Baldi P., Brunak S., Frasconi P., Soda G., Pollastri G.: Exploiting the Past and the Future in Protein Secondary Structure Prediction. Bioinformatics 15 (1999) 937–946
Rost B.: A Neural Network for Prediction of Protein Secondary Structure. In Fiesler, E. and Beale, R. (eds.), Handbook of Neural Computation. IOP Publishing and Oxford University Press (1997), pp. G4.1:1–9.
Ruggiero C., Sacile R., Rauch G.: Peptides Secondary Structure Prediction with Neural Networks: A Criterion for Building Appropriate Learning Sets. Trans. Biomed. Eng. 40 (1993) 1114–1121.
Guermeur Y., Geourjon C., Gallinari P., Deleage G.: Improved Performance in Protein Structure Prediction by Inhomogeneous Score Combination. Bioinformatics 15 (1999) 413–421
Hayward S., Collins J.: Limits on α-Helix Prediction With Neural Network Models. Proteins 14 (1992) 372–381
Baldi P., Brunak S. (eds.): Bioinformatics: The Machine Learning Approach. The MIT Press, London (2000)
Kabsch W., Sander C.: Dictionary of Protein Secondary Structure: Pattern Recognition of Hydrogen-Bonded and Geometrical Features. Biopolymers 22 (1983) 2577–2637
Mitchell T.: Machine Learning. McGraw-Hill, Singapore (1997)
Berman H, Westbrook J., Feng Z., Gilliland G., Bhat T., Weissig H., Shindyalov I., Bourne P.: The Protein Data Bank. Nucleic Acids Research 28 (2000) 235–242.
Siermala M., Juhola M., Vihinen M.: Neural Network Prediction of Polyproline Type II Secondary Structure. In Hasman et al. eds. Medical Infobahn for Europe, Proceedings of MIE2000 and GMDS2000, IOS Press 77 (2000) 475–479
Adzhubei A., Sternberg M.: Left-handed Polyproline II Helices Commonly Occur in Globular Proteins, J. Mol. Biol. 229 (1993) 472–493
Laurikkala, J., Juhola, M., Lammi, S., Penttinen, J., Aukee, P.: Analysis of the Imputed Female Urinary Incontinence D67ata for the Evaluation of Expert System Parameters. Comput. Biol. Med., (2001) 31(4).
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2001 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Siermala, M. (2001). Prediction of Protein Secondary Structures of All Types Using New Hypersphere Machine Learning Method. In: Quaglini, S., Barahona, P., Andreassen, S. (eds) Artificial Intelligence in Medicine. AIME 2001. Lecture Notes in Computer Science(), vol 2101. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48229-6_16
Download citation
DOI: https://doi.org/10.1007/3-540-48229-6_16
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-42294-5
Online ISBN: 978-3-540-48229-1
eBook Packages: Springer Book Archive