Discretization Orders and Efficient Computation of Cartesian Coordinates for Distance Geometry

Douglas Gonçalves 1, 2 Antonio Mucherino 2
2 GenScale - Scalable, Optimized and Parallel Algorithms for Genomics
Inria Rennes – Bretagne Atlantique , IRISA-D7 - GESTION DES DONNÉES ET DE LA CONNAISSANCE
Abstract : Distance Geometry is a class of problems where the position of points in space is to be identified by using information about some relative distances between these points. Although continuous approaches are usually employed, problems belonging to this class can be discretized when some particular assumptions are satisfied. These assumptions strongly depend on the order in which the points to be positioned are considered. We discuss new discretization assumptions that are weaker than previously proposed ones, and present a greedy algorithm for an automatic identification of discretization orders. The use of these weaker assumptions motivates the development of a new method for computing point coordinates. Computational experiments show the effectiveness and efficiency of the proposed approaches when applied to protein instances.
Type de document :
Article dans une revue
Optimization Letters, Springer Verlag, 2014, 8 (7), pp.2111-2125. 〈http://link.springer.com/article/10.1007%2Fs11590-014-0724-z〉
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https://hal.inria.fr/hal-01093049
Contributeur : Antonio Mucherino <>
Soumis le : mercredi 10 décembre 2014 - 09:31:59
Dernière modification le : mercredi 16 mai 2018 - 11:23:35

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  • HAL Id : hal-01093049, version 1

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Douglas Gonçalves, Antonio Mucherino. Discretization Orders and Efficient Computation of Cartesian Coordinates for Distance Geometry. Optimization Letters, Springer Verlag, 2014, 8 (7), pp.2111-2125. 〈http://link.springer.com/article/10.1007%2Fs11590-014-0724-z〉. 〈hal-01093049〉

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