Spectral analysis of microarray gene expression time series data of Plasmodium falciparum

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.

[1]  R. Vautard,et al.  Singular spectrum analysis in nonlinear dynamics, with applications to paleoclimatic time series , 1989 .

[2]  Tuan D. Pham,et al.  Spectral estimation techniques for DNA sequence and microarray data analysis , 2007 .

[3]  Li Liu,et al.  Robust singular value decomposition analysis of microarray data , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Hong Yan,et al.  Parametric Spectral Analysis of Malaria Gene Expression Time Series Data , 2006, CompLife.

[5]  Jonathan E. Allen,et al.  Genome sequence of the human malaria parasite Plasmodium falciparum , 2002, Nature.

[6]  R. Vautard,et al.  Singular-spectrum analysis: a toolkit for short, noisy chaotic signals , 1992 .

[7]  Michael Ruogu Zhang,et al.  Comprehensive identification of cell cycle-regulated genes of the yeast Saccharomyces cerevisiae by microarray hybridization. , 1998, Molecular biology of the cell.

[8]  Hong Yan,et al.  Dominant spectral component analysis for transcriptional regulations using microarray time-series data , 2004, Bioinform..

[9]  Michael Ghil,et al.  Adaptive filtering and maximum entropy spectra with application to changes in atmospheric angular momentum , 1991 .

[10]  J. Derisi,et al.  The Transcriptome of the Intraerythrocytic Developmental Cycle of Plasmodium falciparum , 2003, PLoS biology.

[11]  Patricia De la Vega,et al.  Discovery of Gene Function by Expression Profiling of the Malaria Parasite Life Cycle , 2003, Science.

[12]  P. Lio’,et al.  Periodic gene expression program of the fission yeast cell cycle , 2004, Nature Genetics.

[13]  Eyke Hüllermeier,et al.  Clustering of gene expression data using a local shape-based similarity measure , 2005, Bioinform..

[14]  Andrew L. Rukhin,et al.  Analysis of Time Series Structure SSA and Related Techniques , 2002, Technometrics.

[15]  Hong Yan,et al.  Signal processing for magnetic resonance imaging and spectroscopy , 2002 .

[16]  W. M. Carey,et al.  Digital spectral analysis: with applications , 1986 .

[17]  Hong Yan,et al.  Spectral estimation in unevenly sampled space of periodically expressed microarray time series data. , 2007, BMC bioinformatics.

[18]  R. Offereins.  Book review: Digital control system analysis and design , 1985 .

[19]  Michael Ghil,et al.  Adaptive filtering and prediction of the Southern Oscillation index , 1992 .