Serge Pelet

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Mathematical methods combined with measurements of single-cell dynamics provide a means to reconstruct intracellular processes that are only partly or indirectly accessible experimentally. To obtain reliable reconstructions, the pooling of measurements from several cells of a clonal population is mandatory. However, cell-to-cell variability originating from(More)
Parameterized models of biophysical and mechanical cell properties are important for predictive mathematical modeling of cellular processes. The concepts of turgor, cell wall elasticity, osmotically active volume, and intracellular osmolarity have been investigated for decades, but a consistent rigorous parameterization of these concepts is lacking. Here,(More)
— Robust estimation of kinetic parameters of intra-cellular processes requires large amounts of quantitative data. Due to the high uncertainty of such processes and the fact that recent single-cell measurement techniques have limited resolution and dimensionality, estimation should pool recordings of multiple cells of an isogenic cell population. However,(More)
— Calibration or model parameter estimation from measured data is an ubiquitous problem in engineering. In systems biology this problem turns out to be particularly challenging due to very short data-records, low signal-to-noise ratio of data acquisition, large intrinsic process noise and limited measurement access to only a few, of sometimes several(More)
Protein expression is a dynamic process, which can be rapidly induced by extracellular signals. It is widely appreciated that single cells can display large variations in the level of gene induction. However, the variability in the dynamics of this process in individual cells is difficult to quantify using standard fluorescent protein (FP) expression(More)
The tractability of the budding yeast genome has provided many insights into the fundamental mechanisms regulating cellular life. With the advent of synthetic biology and single-cell measurements, novel tools are required to manipulate the yeast genome in a more controlled manner. We present, here, a new family of yeast shuttle vectors called single(More)
Directional cell growth requires that cells read and interpret shallow chemical gradients, but how the gradient directional information is identified remains elusive. We use single-cell analysis and mathematical modeling to define the cellular gradient decoding network in yeast. Our results demonstrate that the spatial information of the gradient signal is(More)
Mitogen activated protein kinases (MAPK) play an essential role in integrating extra-cellular signals and intra-cellular cues to allow cells to grow, adapt to stresses, or undergo apoptosis. Budding yeast serves as a powerful system to understand the fundamental regulatory mechanisms that allow these pathways to combine multiple signals and deliver an(More)
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