Spectral analysis of microarray gene expression time series data of Plasmodium falciparum
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We propose a new strategy to analyze 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 modeling, 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.
International Journal of Bioinformatics Research and Applications
© 2008 Inderscience Publishers. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal website for access to the definitive, published version.