The structural classes of proteins predicted by multi-resolution analysis

  • Authors:

  • Jing Zhao;Peiming Song;Linsen Xie;Jianhua Luo

  • Affiliations:

  • School of Life Science & Technology, Shanghai Jiaotong University, Shanghai;School of Life Science & Technology, Shanghai Jiaotong University, Shanghai;Lishui College, Lishui, Zhejiang;School of Life Science & Technology, Shanghai Jiaotong University, Shanghai

  • Venue:
  • CIS'04 Proceedings of the First international conference on Computational and Information Science
  • Year:
  • 2004

Quantified Score

Hi-index 0.00

Visualization

Abstract

Prediction of protein structural class from primary structure is studied in this paper. Wavelet packet transform is used to decompose the corresponding numerical signal of protein into several sub-signals at different resolution scales. The auto-correlation functions based on the sub-signals are used as feature vectors of the protein. The Bayes decision rule is used as classification algorithm. Experiments show that for the same datasets, the prediction accuracy is improved compared with the existed methods.