Predicting functional sites in biological sequences using canonical correlation analysis

Alvaro J. González; Li Liao; Cathy H. Wu

doi:10.1109/BIBMW.2009.5332095

2009 IEEE International Conference on Bioinformatics and Biomedicine Workshop

Predicting functional sites in biological sequences using canonical correlation analysis

Year: 2009, Pages: 347

DOI Bookmark: 10.1109/BIBMW.2009.5332095

Authors

Alvaro J. González, Department of Computer and Information Sciences, University of Delaware, Newark, Delaware
Li Liao, Department of Computer and Information Sciences, University of Delaware, Newark, Delaware
Cathy H. Wu, Department of Computer and Information Sciences, University of Delaware, Newark, Delaware

Abstract

Protein functional site prediction plays a key role in understanding protein function and in protein engineering. In this work we developed a novel method using canonical correlation analysis to predict protein ligand binding sites. The method was tested with a well-known benchmark dataset and consistently outperformed the existing method Xdet, which is based on Pearson correlation, by improving the lowest and highest ranked positives for more than 18% and 22% respectively.

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Predicting functional sites in biological sequences using canonical correlation analysis

Authors

Abstract

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