Identifying Protein Structural Classes by a Fusion Sequence Encoding Scheme

Tong Wang; An Bao Wang; Qing Hua Huang

doi:10.4028/www.scientific.net/AMM.58-60.843

Paper Titles

Fabrication of Plastic Micro Features on Microporous Mold by Hot Embossing
p.822

Design Optimization of Savonius Rotors: An Overview
p.827

Calibration of Probe of Cloud Droplet Based on Forward Scattering
p.834

Application of Isomap Method in Prediction of Protein Quaternary Structure
p.840

Identifying Protein Structural Classes by a Fusion Sequence Encoding Scheme
p.843

Establishing Integration Process during Engineering Design
p.848

The Development of Virtual Manufacturing Technology
p.854

The Characteristics and Application of Reconfigurable System
p.859

Computer and Network Oriented Welding Power Source Design
p.864

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 58-60Identifying Protein Structural Classes by a Fusion...

Identifying Protein Structural Classes by a Fusion Sequence Encoding Scheme

Abstract:

In this study, a novel sequence encoding scheme is introduced by fusing PseAA and PSSM. However, this sequence encoding scheme would correspond to a very high dimensional feature vector. A dimensionality reduction algorithm, the so-called NPE (Neighborhood Preserving Embedding) is introduced to extract the key features from the high-dimensional space. Finally, the K-NN (K-Nearest Neighbor) classifier is employed to identify the types of protein structures. Our jackknife test results thus obtained are quite encouraging, which indicate that the above methods are used effectively to deal with this complicated problem of predicting protein structural classes.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 58-60)

Pages:

843-847

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.58-60.843

Citation:

Cite this paper

Online since:

June 2011

Authors:

Tong Wang, An Bao Wang, Qing Hua Huang

Keywords:

Fusion Sequence Encoding Scheme, NPE, Protein Structural Class

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] G. Zhou, Xu X, Zhang CT: A weighting method for predicting protein structural class from amino acid composition. Eur J Biochem. Vol. 210 (1992), pp.747-749.

DOI: 10.1111/j.1432-1033.1992.tb17476.x

Google Scholar

[2] C. T. Zhang, K. C. Chou. An optimization approach to predicting protein structural class from amino acid composition. Protein Sci. Vol. 1 (1992), pp.401-408.

DOI: 10.1002/pro.5560010312

Google Scholar

[3] K.C. Chou. Prediction of protein cellular attributes using pseudo amino acid composition. Proteins Struct Funct Genet. Vol. 44 (2001), p.246–255.

DOI: 10.1002/prot.1035

Google Scholar

[4] Z.C. Li, X.B. Zhou, Z. Dai, X.Y. Zou. Prediction of protein structural classes by Chou's pseudo amino acid composition: approached using continuous wavelet transform and principal component analysis Amino Acids. vol. 37 (2009), pp.415-25.

DOI: 10.1007/s00726-008-0170-2

Google Scholar

[5] X. He, D. Cai, S. Yan, and H. -J. Zhang. Neighborhood Preserving Embedding. IEEE International Conference on Computer Vision (ICCV) (2005), Beijing, China.

DOI: 10.1109/iccv.2005.167

Google Scholar

[6] K.C. Chou. A key driving force in determination of protein structural classes. Biochem. Biophys. Res. Commun. vol. 264 (1999), p.216–224.

Google Scholar