Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution

@inproceedings{SiegalGaskins2009ModelBasedDO,
  title={Model-Based Deconvolution of Cell Cycle Time-Series Data Reveals Gene Expression Details at High Resolution},
  author={Dan Siegal-Gaskins and Joshua N. Ash and Sean Crosson},
  booktitle={PLoS Computational Biology},
  year={2009}
}
In both prokaryotic and eukaryotic cells, gene expression is regulated across the cell cycle to ensure "just-in-time" assembly of select cellular structures and molecular machines. However, present in all time-series gene expression measurements is variability that arises from both systematic error in the cell synchrony process and variance in the timing of cell division at the level of the single cell. Thus, gene or protein expression data collected from a population of synchronized cells is… CONTINUE READING

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