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Risk factors for prosthetic joint infection: case-control study
Authors:EF Berbari  AD Hanssen  MC Duffy  JM Steckelberg  DM Ilstrup  WS Harmsen  DR Osmon
Affiliation:Department of Chemistry and Biochemistry, University of California, San Diego, La Jolla 92093-0365, USA. wriggers@ucsd.edu
Abstract:Topology-representing neural networks are employed to generate pseudo-atomic structures of large-scale protein assemblies by combining high-resolution data with volumetric data at lower resolution. As an application example, actin monomers and structural subdomains are located in a three-dimensional (3D) image reconstruction from electron micrographs. To test the reliability of the method, the resolution of the atomic model of an actin polymer is lowered to a level typically encountered in electron microscopic reconstructions. The atomic model is restored with a precision nine times the nominal resolution of the corresponding low-resolution density. The presented self-organizing computing method may be used as an information-processing tool for the synthesis of structural data from a variety of biophysical sources.
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