Bulletin of the American Physical Society
APS March Meeting 2011
Volume 56, Number 1
Monday–Friday, March 21–25, 2011; Dallas, Texas
Session X38: Focus Session: Non-Equilibrium Insights into Single Molecules and Cell Function I |
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Sponsoring Units: DCP DBP Chair: Norbert Scherer, University of Chicago Room: A130/131 |
Thursday, March 24, 2011 2:30PM - 3:06PM |
X38.00001: The Statistical Mechanics of Trajectories and Weights: Applications to Gene Expression Invited Speaker: Many fascinating questions concerning the behavior of systems ranging from chemical reaction patterns to the patterns of gene expression in living systems do not concern their terminal states, but rather the various microscopic trajectories connecting those states. Some of the most intriguing examples of these kinds of phenomena center on the time evolution of the many molecular machines that populate living cells. Motivated by studies of the time evolution of gene expression, this talk will review both classic approaches to time evolution using rate equations (but couched in the language of trajectories and weights) and more controversial ideas based upon the principle of maximum entropy. [Preview Abstract] |
Thursday, March 24, 2011 3:06PM - 3:42PM |
X38.00002: Challenges in Characterizing and Controlling Complex Cellular Systems Invited Speaker: Multicellular dynamic biological processes such as developmental differentiation, wound repair, disease, aging, and even homeostasis can be represented by trajectories through a phase space whose extent reflects the genetic, post-translational, and metabolic complexity of the process - easily extending to tens of thousands of dimensions. Intra- and inter-cellular sensing and regulatory systems and their nested, redundant, and non-linear feed-forward and feed-back controls create high-dimensioned attractors in this phase space. Metabolism provides free energy to drive non-equilibrium processes and dynamically reconfigure attractors. Studies of single molecules and cells provide only minimalist projections onto a small number of axes. It may be difficult to infer larger-scale emergent behavior from linearized experiments that perform only small amplitude perturbations on a limited number of the dimensions. Complete characterization may succeed for bounded component problems, such as an individual cell cycle or signaling cascade, but larger systems problems will require a coarse-grained approach. Hence a new experimental and analytical framework is needed. Possibly one could utilize high-amplitude, multi-variable driving of the system to infer coarse-grained, effective models, which in turn can be tested by their ability to control systems behavior. Navigation at will between attractors in a high-dimensioned dynamical system will provide not only detailed knowledge of the shape of attractor basins, but also measures of underlying stochastic events such as noise in gene expression or receptor binding and how both affect system stability and robustness. Needed for this are wide-bandwidth methods to sense and actuate large numbers of intracellular and extracellular variables and automatically and rapidly infer dynamic control models. The success of this approach may be determined by how broadly the sensors and actuators can span the full dimensionality of the phase space. [Preview Abstract] |
Thursday, March 24, 2011 3:42PM - 4:18PM |
X38.00003: Maximizing efficiency of molecular machines Invited Speaker: I will discuss how to locate protocols that minimize dissipation in non-equilibrium, molecular scale processes, adapting ideas from finite-time thermodynamics. [Preview Abstract] |
Thursday, March 24, 2011 4:18PM - 4:54PM |
X38.00004: Autonomous Boolean models for logic, timing, and stability in regulatory networks Invited Speaker: The dynamics of gene expression in a cell is controlled by a dizzying array of biochemical processes. Natural selection, however, has created regulatory systems with a level of logical organization that can be modeled without detailed knowledge of the biochemistry. In cases where graded responses are not relevant, autonomous Boolean network (ABN) models can effectively represent the logic of gene regulation. These are models in which Boolean logic governs the output value of each node and the timing of updates is determined according to delay parameters associated with each link. An advantage of ABNs over synchronous or random asynchronous Boolean networks is that noise associated with molecular concentrations or transport times can be represented through fluctuations in the timing of updates. We have used ABN models to investigate the stability of oscillations in a model of transcriptional oscillations in yeast and the parameter constraints in a model of segment polarity maintenance in the fly embryo, and also to characterize chaotic dynamics observed in a free--running digital electronic circuit. The yeast study highlights architectural and dynamical features of oscillators that rely on pulse transmission rather than a frustrated feedback loop; the fly study reveals timing constraints that are hidden in ODE models; and the electronics study shows that Boolean chaos can occur if and only if time delays are history dependent. [Preview Abstract] |
Thursday, March 24, 2011 4:54PM - 5:06PM |
X38.00005: Maximum Caliber Analysis of Ion-Channel Gating Roy Campbell The principle of maximum caliber, MaxCal, is a generalization to nonequilibrium statistical mechanics of the principle of maximum entropy, MaxEnt. E. T. Jaynes introduced the MaxEnt approach to equilibrium statistical mechanics in 1957 and its MaxCal generalization in 1980. MaxCal has recently been used to derive dynamical laws of transport, analyze single particle two-state dynamics, and study few state models of non-equilibrium processes. We use MaxCal to analyze ion-channel gating data and make logical inferences concerning the underlying dynamics. The inferred trajectory probabilities are used to calculate the fluctuations responsible for channel noise. [Preview Abstract] |
Thursday, March 24, 2011 5:06PM - 5:18PM |
X38.00006: Driving denaturation: Nanoscale thermal transport as a probe of DNA melting Yonatan Dubi, Kirill Velizhanin, Chih-Chun Chien, Michael Zwolak The microscopic dynamics of DNA denaturation have long been a subject of intense study but many aspects of this phenomenon remain poorly understood. Experiments typically measure the degree of denaturation versus temperature which, unfortunately, introduces only a relatively weak constraint: Although many existing models reproduce this denaturation transition well, they give, e.g., incorrect time scales for fluctuations in base pair unbinding. Here, we propose a critical test of DNA models based on driving DNA out of thermal equilibrium via two heat reservoirs. Contrary to what might be expected, we find that the preeminent model of denaturation predicts the thermal conductance to increase substantially as DNA melts. Furthermore, we show that different models can possess qualitatively different thermal transport properties. Measuring the thermal conductance of DNA will thus shed new light on the nonlinear physics of this important molecule and may lead to novel thermal technologies, such as a DNA thermal switch. [Preview Abstract] |
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