Authors: Liping Du, Shuanhu Wu, Alan Wee-Chung Liew, David K. Smith, Hong Yan
Addresses: Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong; School of Information Engineering, University of Science and Technology, Beijing 100083, China. ' Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong; School of Computer Science and Technology, Yantai University, Shandong, Yantai 264005, China. ' School of Information and Communication Technology, Griffith University, Gold Coast Campus, QLD4222, Queensland, Australia. ' Department of Biochemistry, University of Hong Kong, Pok Fu Lam, Hong Kong. ' Department of Electronic Engineering, City University of Hong Kong, Tat Chee Avenue, Kowloon, Hong Kong; School of Electronic and Information Engineering, University of Sydney, NSW2006, Sydney, Australia
Abstract: We propose a new strategy to analyse the periodicity of gene expression profiles using Singular Spectrum Analysis (SSA) and Autoregressive (AR) model based spectral estimation. By combining the advantages of SSA and AR modelling, more periodic genes are extracted in the Plasmodium falciparum data set, compared with the classical Fourier analysis technique. We are able to identify more gene targets for new drug discovery, and by checking against the seven well-known malaria vaccine candidates, we have found five additional genes that warrant further biological verification.
Keywords: singular spectrum analysis; SSA; autoregressive spectral estimation model; microarray time series analysis; gene target; plasmodium falciparum; bioinformatics; drug discovery; gene expression profiles.
International Journal of Bioinformatics Research and Applications, 2008 Vol.4 No.3, pp.337 - 349
Available online: 17 Jul 2008 *Full-text access for editors Access for subscribers Purchase this article Comment on this article