Dynamical Analysis of Circadian gene expression

CARLA LAYANA; LUIS DIAMBRA

International Journal of Biological and Medical Sciences

World Academy of Science, Engineering and Technology

Lugar: París; Año: 2008 vol. 3 p. 101 - 105

2070-3791

Microarrays technique allows the simultaneous  measurements of the expression levels of thousands of mRNAs. By mining this data one can identify the dynamics of the gene expression time series. By recourse of principal component analysis, we uncover the circadian rhythmic patterns underlying the gene expression profiles from Cyanobacterium Synechocystis. We applied PCA to reduce the dimensionality of the data set. Examination of the components also provides insight into the underlying factors measured in the experiments. Our results suggest that all rhythmic content of data can be reduced to three main components.