Summary
Several recent advances in both the theory and algorithms for the application of Distance Geometry are reported. These advances were developed with the application to Protein Folding and Drug Design in mind. However, several results are of general interest and are applicable in statistics and the social sciences where the corresponding problems are known as multidimensional scaling. The spectral gradient algorithm is proposed as an alternate method to the majorization algorithm for solving the metric stress problem. The ALS Algorithm that is used to determine molecular conformations is similar to the alternating least squares approach used in nonmetric multidimensional scaling. Several theorems relating geometric structure and the properties of distance matrices are explored. These include a geometrical characterization of the structures which comprise a face of the cone of Euclidean distance matrices. The structure of Euclidean matrices which arise from points which lie on the surface of a hypersphere are investigated.
This work was partially supported by NSF Grant CHE-9301120.
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Hayden, T.L. (1994). Applications of Distance Geometry to Molecular Conformation. In: Diday, E., Lechevallier, Y., Schader, M., Bertrand, P., Burtschy, B. (eds) New Approaches in Classification and Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-51175-2_41
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DOI: https://doi.org/10.1007/978-3-642-51175-2_41
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