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Molecular distance geometry methods: From continuous to discrete

  • Leo Liberti
  • , Carlile Lavor
  • , Antonio Mucherino
  • , Nelson Maculan

Research output: Contribution to journalArticlepeer-review

Abstract

Distance geometry problems (DGP) arise from the need to position entities in the Euclidean K-space given some of their respective distances. Entities may be atoms (molecular distance geometry), wireless sensors (sensor network localization), or abstract vertices of a graph (graph drawing). In the context of molecular distance geometry, the distances are usually known because of chemical properties and nuclear magnetic resonance experiments; sensor networks can estimate their relative distance by recording the power loss during a two-way exchange; finally, when drawing graphs in two or three dimensions, the graph to be drawn is given, and therefore distances between vertices can be computed. DGPs involve a search in a continuous Euclidean space, but sometimes the problem structure helps reduce the search to a discrete set of points. In this paper we survey some continuous and discrete methods for solving some problems of molecular distance geometry.

Original languageEnglish
Pages (from-to)33-51
Number of pages19
JournalInternational Transactions in Operational Research
Volume18
Issue number1
DOIs
Publication statusPublished - 1 Jan 2011

Keywords

  • Distance geometry
  • Optimization
  • Protein conformation

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