We are designing and developing a novel software environment -- the Digital Material -- to suppor... more We are designing and developing a novel software environment -- the Digital Material -- to support materials modeling across many length and time scales, in order to develop improved descriptions of material structure and evolution. Software support is required for high-performance numerical kernels, lightweight infrastructures for prototyping, steering and analysis, information transfer across scales, coupling of disparate simulation modules, and
For the site dilution model on the hypercubic lattice Zd, d b 2, we examine the density of states... more For the site dilution model on the hypercubic lattice Zd, d b 2, we examine the density of states for the tight-binding Hamiltonian projected onto the infinite cluster. It is shown that, with probability one, the corresponding integrated density of states is discontinuous on a set of energies which is dense in the band. This result is proved by constructing
We apply the ideas of optimal experimental design to systems biology models: minimizing a design ... more We apply the ideas of optimal experimental design to systems biology models: minimizing a design criterion based on the average variance of predictions, we suggest new experiments that need to be performed to optimally test a given biological hypothesis. The estimated variance in predictions is derived from the sensitivities of protein and chemical species in the model to changes in
Quantitative models of complex biological systems often possess dozens of unknown parameters. We ... more Quantitative models of complex biological systems often possess dozens of unknown parameters. We argue that such systems are universally ``sloppy''; their behaviors are orders of magnitude more sensitive to moves in some directions in parameter space than others. To establish this, we survey models from the literature and show that their ``complete and perfect data'' Fisher Information Matrices possess eigenvalues
Directly measuring the parameters involved in dynamical models of cellular processes is typically... more Directly measuring the parameters involved in dynamical models of cellular processes is typically very difficult, and collectively fitting such parameters to other data often yields large parameter uncertainties. Nonetheless, a collective fit which only weakly constrains model parameters may strongly constrain model predictions, if the model is ill-conditioned: much more sensitive to some directions in parameter space than others. In
Quantitative computational models play an increasingly important role in modern biology. Such mod... more Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling
... Page 3. JOEL D. SHORE, MARK HOLZER,AND JAMES P. SETHNA ... Thus, unlike in two dimensions, th... more ... Page 3. JOEL D. SHORE, MARK HOLZER,AND JAMES P. SETHNA ... Thus, unlike in two dimensions, the total bar-rier to flip all the spins along an edge is proportional to the linear size, L, of the domain; and the time to shrink the domain is now exponential in L. Page 4. ...
Optical trapping is a powerful single molecule technique used to study dynamic biomolecular event... more Optical trapping is a powerful single molecule technique used to study dynamic biomolecular events, especially those involving DNA and DNA-binding proteins. Current implementations usually involve only one of stretching, unzipping, or twisting DNA along one dimension. To expand the capabilities of optical trapping for more complex measurements would require a multidimensional technique that combines all of these manipulations in a single experiment. Here, we report the development and utilization of such a novel optical trapping assay based on a three-branch DNA construct, termed a "Y structure". This multidimensional assay allows precise, real-time tracking of multiple configurational changes. When the Y structure template is unzipped under both force and torque, the force and extension of all three branches can be determined simultaneously. Moreover, the assay is readily compatible with fluorescence, as demonstrated by unzipping through a fluorescently labeled, paused tr...
We study the crossover scaling behavior of the height-height correlation function in interface de... more We study the crossover scaling behavior of the height-height correlation function in interface depinning in random media. We analyze experimental data from a fracture experiment and simulate an elastic line model with nonlinear couplings and disorder. Both exhibit a crossover between two different universality classes. For the experiment, we fit a functional form to the universal crossover scaling function. For the model, we vary the system size and the strength of the nonlinear term and describe the crossover between the two universality classes with a multiparameter scaling function. Our method provides a general strategy to extract scaling properties in depinning systems exhibiting crossover phenomena.
Large scale models of physical phenomena demand the development of new statistical and computatio... more Large scale models of physical phenomena demand the development of new statistical and computational tools in order to be effective. Many such models are "sloppy," i.e., exhibit behavior controlled by a relatively small number of parameter combinations. We review an information theoretic framework for analyzing sloppy models. This formalism is based on the Fisher information matrix, which is interpreted as a Riemannian metric on a parameterized space of models. Distance in this space is a measure of how distinguishable two models are based on their predictions. Sloppy model manifolds are bounded with a hierarchy of widths and extrinsic curvatures. The manifold boundary approximation can extract the simple, hidden theory from complicated sloppy models. We attribute the success of simple effective models in physics as likewise emerging from complicated processes exhibiting a low effective dimensionality. We discuss the ramifications and consequences of sloppy models for biochemistry and science more generally. We suggest that the reason our complex world is understandable is due to the same fundamental reason: simple theories of macroscopic behavior are hidden inside complicated microscopic processes.
We are designing and developing a novel software environment -- the Digital Material -- to suppor... more We are designing and developing a novel software environment -- the Digital Material -- to support materials modeling across many length and time scales, in order to develop improved descriptions of material structure and evolution. Software support is required for high-performance numerical kernels, lightweight infrastructures for prototyping, steering and analysis, information transfer across scales, coupling of disparate simulation modules, and
For the site dilution model on the hypercubic lattice Zd, d b 2, we examine the density of states... more For the site dilution model on the hypercubic lattice Zd, d b 2, we examine the density of states for the tight-binding Hamiltonian projected onto the infinite cluster. It is shown that, with probability one, the corresponding integrated density of states is discontinuous on a set of energies which is dense in the band. This result is proved by constructing
We apply the ideas of optimal experimental design to systems biology models: minimizing a design ... more We apply the ideas of optimal experimental design to systems biology models: minimizing a design criterion based on the average variance of predictions, we suggest new experiments that need to be performed to optimally test a given biological hypothesis. The estimated variance in predictions is derived from the sensitivities of protein and chemical species in the model to changes in
Quantitative models of complex biological systems often possess dozens of unknown parameters. We ... more Quantitative models of complex biological systems often possess dozens of unknown parameters. We argue that such systems are universally ``sloppy''; their behaviors are orders of magnitude more sensitive to moves in some directions in parameter space than others. To establish this, we survey models from the literature and show that their ``complete and perfect data'' Fisher Information Matrices possess eigenvalues
Directly measuring the parameters involved in dynamical models of cellular processes is typically... more Directly measuring the parameters involved in dynamical models of cellular processes is typically very difficult, and collectively fitting such parameters to other data often yields large parameter uncertainties. Nonetheless, a collective fit which only weakly constrains model parameters may strongly constrain model predictions, if the model is ill-conditioned: much more sensitive to some directions in parameter space than others. In
Quantitative computational models play an increasingly important role in modern biology. Such mod... more Quantitative computational models play an increasingly important role in modern biology. Such models typically involve many free parameters, and assigning their values is often a substantial obstacle to model development. Directly measuring in vivo biochemical parameters is difficult, and collectively fitting them to other experimental data often yields large parameter uncertainties. Nevertheless, in earlier work we showed in a growth-factor-signaling
... Page 3. JOEL D. SHORE, MARK HOLZER,AND JAMES P. SETHNA ... Thus, unlike in two dimensions, th... more ... Page 3. JOEL D. SHORE, MARK HOLZER,AND JAMES P. SETHNA ... Thus, unlike in two dimensions, the total bar-rier to flip all the spins along an edge is proportional to the linear size, L, of the domain; and the time to shrink the domain is now exponential in L. Page 4. ...
Optical trapping is a powerful single molecule technique used to study dynamic biomolecular event... more Optical trapping is a powerful single molecule technique used to study dynamic biomolecular events, especially those involving DNA and DNA-binding proteins. Current implementations usually involve only one of stretching, unzipping, or twisting DNA along one dimension. To expand the capabilities of optical trapping for more complex measurements would require a multidimensional technique that combines all of these manipulations in a single experiment. Here, we report the development and utilization of such a novel optical trapping assay based on a three-branch DNA construct, termed a "Y structure". This multidimensional assay allows precise, real-time tracking of multiple configurational changes. When the Y structure template is unzipped under both force and torque, the force and extension of all three branches can be determined simultaneously. Moreover, the assay is readily compatible with fluorescence, as demonstrated by unzipping through a fluorescently labeled, paused tr...
We study the crossover scaling behavior of the height-height correlation function in interface de... more We study the crossover scaling behavior of the height-height correlation function in interface depinning in random media. We analyze experimental data from a fracture experiment and simulate an elastic line model with nonlinear couplings and disorder. Both exhibit a crossover between two different universality classes. For the experiment, we fit a functional form to the universal crossover scaling function. For the model, we vary the system size and the strength of the nonlinear term and describe the crossover between the two universality classes with a multiparameter scaling function. Our method provides a general strategy to extract scaling properties in depinning systems exhibiting crossover phenomena.
Large scale models of physical phenomena demand the development of new statistical and computatio... more Large scale models of physical phenomena demand the development of new statistical and computational tools in order to be effective. Many such models are "sloppy," i.e., exhibit behavior controlled by a relatively small number of parameter combinations. We review an information theoretic framework for analyzing sloppy models. This formalism is based on the Fisher information matrix, which is interpreted as a Riemannian metric on a parameterized space of models. Distance in this space is a measure of how distinguishable two models are based on their predictions. Sloppy model manifolds are bounded with a hierarchy of widths and extrinsic curvatures. The manifold boundary approximation can extract the simple, hidden theory from complicated sloppy models. We attribute the success of simple effective models in physics as likewise emerging from complicated processes exhibiting a low effective dimensionality. We discuss the ramifications and consequences of sloppy models for biochemistry and science more generally. We suggest that the reason our complex world is understandable is due to the same fundamental reason: simple theories of macroscopic behavior are hidden inside complicated microscopic processes.
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Papers by James Sethna