Predicting functional sites in biological sequences using canonical correlation analysis

Author

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

Author_Institution

Dept. of Comput. & Inf. Sci., Univ. of Delaware, Newark, DE, USA

fYear

2009

fDate

1-4 Nov. 2009

Firstpage

347

Lastpage

347

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.

Keywords

biology computing; correlation methods; proteins; vectors; Pearson correlation; biological sequences; canonical correlation analysis; protein engineering; protein functional site prediction; protein ligand binding sites; Amino acids; Benchmark testing; Biochemistry; Bioinformatics; Biology computing; Information analysis; Mutual information; Protein engineering; Random variables; Rotation measurement; canonical correlation analysis; functional residue; specificity determining position;

fLanguage

English

Publisher

ieee

Conference_Titel

Bioinformatics and Biomedicine Workshop, 2009. BIBMW 2009. IEEE International Conference on

Conference_Location

Washington, DC

Print_ISBN

978-1-4244-5121-0

Type

conf

DOI

10.1109/BIBMW.2009.5332095

Filename

5332095