Solving the molecular distance geometry problem with inaccurate distance data

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 presente...

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Detalles Bibliográficos
Autores principales: Souza, Michael, Lavor, Carlile, Muritiba, Albert, Maculan, Nelson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Methodology Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3698034/
https://www.ncbi.nlm.nih.gov/pubmed/23901894
http://dx.doi.org/10.1186/1471-2105-14-S9-S7
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author Souza, Michael
Lavor, Carlile
Muritiba, Albert
Maculan, Nelson
author_facet Souza, Michael
Lavor, Carlile
Muritiba, Albert
Maculan, Nelson
author_sort Souza, Michael
collection PubMed
description 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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spelling pubmed-36980342013-07-02 Solving the molecular distance geometry problem with inaccurate distance data Souza, Michael Lavor, Carlile Muritiba, Albert Maculan, Nelson BMC Bioinformatics Methodology Article 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. BioMed Central 2013-06-28 /pmc/articles/PMC3698034/ /pubmed/23901894 http://dx.doi.org/10.1186/1471-2105-14-S9-S7 Text en Copyright © 2013 Souza et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methodology Article
Souza, Michael
Lavor, Carlile
Muritiba, Albert
Maculan, Nelson
Solving the molecular distance geometry problem with inaccurate distance data
title Solving the molecular distance geometry problem with inaccurate distance data
title_full Solving the molecular distance geometry problem with inaccurate distance data
title_fullStr Solving the molecular distance geometry problem with inaccurate distance data
title_full_unstemmed Solving the molecular distance geometry problem with inaccurate distance data
title_short Solving the molecular distance geometry problem with inaccurate distance data
title_sort solving the molecular distance geometry problem with inaccurate distance data
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3698034/
https://www.ncbi.nlm.nih.gov/pubmed/23901894
http://dx.doi.org/10.1186/1471-2105-14-S9-S7
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AT muritibaalbert solvingthemoleculardistancegeometryproblemwithinaccuratedistancedata
AT maculannelson solvingthemoleculardistancegeometryproblemwithinaccuratedistancedata

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