about the workshop

Cells are subject to vast amounts of random variation, which can cause isogenic cells to respond differently, despite identical environmental conditions. Recent experimental techniques make it possible to measure this variation in gene expression, protein abundance, and cellular behavior. Combined with computational modeling, these techniques enable us to uncover the causes and effects of stochastic cellular dynamics. Depending on cellular function, biochemical processes may act to minimize stochastic variations or exploit them to the cell's advantage; in both cases, cellular processes have evolved to be remarkably robust to both intrinsic and extrinsic noise. By exploring this robustness in naturally occurring biological systems, we hope not only to improve our understanding of cellular biology, but also to formulate the "design principles" necessary to build similarly robust biochemical circuits and nanoscale devices.

In this workshop, we will bring together several experts from different aspects of this exciting research topic. First, we will hear from experimental molecular biologists, who are continually developing and perfecting new quantitative techniques to observe single cell and single molecule dynamics. Tools such as flow cytometry and fluorescence activated cell sorting (FACS) enable researchers to measure the protein levels for millions of individual living cells in the time span of a single minute--thus conducting millions of simultaneous experiments. Time-lapse fluorescence microscopy and microfluidics have made it possible for researchers to measure, track and manipulate the behavior of single cells in carefully controlled micro-environments. Fluorescence in situ hybridization (FISH) techniques enable researchers to explore the spatial distributions of specific RNA molecule within a cell.

Next, the theorists and mathematicians among us will present new quantitative methods to analyze and explain the vast amounts of statistical data gathered from such experiments. It is known that stochasticity in cells is caused in part by intrinsic noise - the variability caused by the statistical dynamics of a chemical reaction with a small number of reactants - and in part by extrinsic noise - the variability caused by random fluctuations in a cell's environment. The participants in this workshop have already developed many methods to understand and differentiate between these types of noise in experimental data. In addition, as experimental techniques such as FISH provide more and more information on the spatial dynamics of intracellular processes, it becomes more useful to extend these techniques to spatially heterogenous reaction dynamics.

Finally, these theorists and experimentalists can integrate their various analyses to understand how, why and when different cellular mechanisms transmit noise in different ways, i.e. some suppress it while others amplify or exploit it. For example, control theory can help us understand feedback and feedforward regulatory motifs in cellular architectures, while an information theoretic perspective can help us to understand how cells in a developing multicellular organism can determine their exact spatial location. These analyses suggest new methods and appropriate models for mathematically demonstrating how certain motifs are useful for dealing with noise and uncertainty. Such analyses are then directly applicable to the work of more applied researchers, who can use these theories to better constructing synthetic biological circuits and devices at the nanoscale level, including biomolecular motors and DNA molecular machines.