Dynamical Analysis of Circadian Gene Expression

C. LAYANA; L. DIAMBRA

International Journal of Biological, Biomedical and Medical Sciences

World Academy of Science, Engineering and Technology

Año: 2008 vol. 3 p. 101 - 105

2070-3791

Microarrays technique allows the simultaneousmeasurements of the expression levels of thousands of mRNAs. Bymining this data one can identify the dynamics of the geneexpression time series. By recourse of principal component analysis,we uncover the circadian rhythmic patterns underlying the geneexpression profiles from Cyanobacterium Synechocystis. We appliedPCA to reduce the dimensionality of the data set. Examination of thecomponents also provides insight into the underlying factorsmeasured in the experiments. Our results suggest that all rhythmiccontent of data can be reduced to three main components.