Maximum Entropy deconvolution method for precise timing of gene expression
Mathematics, The University of Toledo
(April 15, 2009 4:00 PM - 5:00 PM)
In the microarray experiments, the measured mRNA levels are averaged over cell population thus imperfectly reflecting single cell expression profiles. We developed a deconvolution method, using Maximum Entropy principle, that allows for reliable estimations of the single cell mRNA levels from time course microarray data in cases the population synchrony can be modelled. Applying this method to data from a synchronized baker's yeast culture we were able to time the peaks of expression of transcriptionally regulated cell cycle genes to an accuracy of 2 min (~1% of the cell cycle time), an order of magnitude better resolution than in the original data. Our results reveal distinct subphases of the cell cycle undetectable by morphological observation, as well as the precise timeline of macromolecular complex assembly during key cell cycle events.