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Solving the molecular distance geometry problem with inaccurate distance data
Michael Souza1, Carlile Lavor, Albert Muritiba
1Department of Statistics and Applied Mathematics, Federal University of Ceará, Ceará, 60455-760, Brazil. michael@ufc.br
Abstract:
We present a new iterative algorithm for the molecular distance geometry problem with inaccurate and sparse data, which is based on the solution of linear systems, maximum cliques, and a minimization of nonlinear least-squares function. Computational results with real protein structures are presented in order to validate our approach.
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