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dc.contributor.author Kim, Haram
dc.contributor.author Brookes, Emre
dc.contributor.author Cao, Weiming
dc.contributor.author Demeler, Borries
dc.date.accessioned 2021-09-22T19:08:21Z
dc.date.available 2021-09-22T19:08:21Z
dc.date.issued 2018
dc.identifier.citation Kim, H., Brookes, E., Cao, W., & Demeler, B. (2018). Two-dimensional grid optimization for sedimentation velocity analysis in the analytical ultracentrifuge. European Biophysics Journal, 47(7), 837-844. https://doi.org/10.1007/s00249-018-1309-z en_US
dc.identifier.uri https://hdl.handle.net/10133/6031
dc.description Accepted author manuscript en_US
dc.description.abstract Sedimentation velocity experiments performed in the analytical ultracentrifuge are modeled using finite-element solutions of the Lamm equation. During modeling, three fundamental parameters are optimized: the sedimentation coefficients, the diffusion coefficients, and the partial concentrations of all solutes present in a mixture. A general modeling approach consists of fitting the partial concentrations of solutes defined in a two-dimensional grid of sedimentation and diffusion coefficient combinations that cover the range of possible solutes for a given mixture. An increasing number of grid points increase the resolution of the model produced by the subsequent analysis, with denser grids giving rise to a very large system of equations. Here, we evaluate the efficiency and resolution of several regular grids and show that traditionally defined grids tend to provide inadequate coverage in one region of the grid, while at the same time being computationally wasteful in other sections of the grid. We describe a rapid and systematic approach for generating efficient two-dimensional analysis grids that balance optimal information content and model resolution for a given signal-to-noise ratio with improved calculation efficiency. These findings are general and apply to one- and two-dimensional grids, although they no longer represent regular grids. We provide a recipe for an improved grid-point spacing in both directions which eliminates unnecessary points, while at the same time providing a more uniform resolution that can be scaled based on the stochastic noise in the experimental data. en_US
dc.language.iso en_US en_US
dc.publisher Springer en_US
dc.subject Computational biophysics en_US
dc.subject Analytical ultracentrifugation en_US
dc.subject Numerical optimization en_US
dc.subject Velocity analysis
dc.subject Two-dimensional grids
dc.subject.lcsh Hydrodynamics
dc.subject.lcsh High performance computing
dc.subject.lcsh Centrifuges
dc.title Two-dimensional grid optimization for sedimentation velocity analysis in the analytical ultracentrifuge en_US
dc.type Article en_US
dc.publisher.faculty Arts and Science en_US
dc.publisher.department Department of Chemistry and Biochemistry en_US
dc.description.peer-review Yes en_US
dc.publisher.institution Cornell University en_US
dc.publisher.institution University of Texas Health Science Center at San Antonio en_US
dc.publisher.institution University of Texas at San Antonio en_US
dc.publisher.institution University of Lethbridge en_US
dc.publisher.url https://doi.org/10.1007/s00249-018-1309-z en_US


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