Molecular distance geometry methods: from continuous to discrete

dc.creatorLiberti, L
dc.creatorLavor, C
dc.creatorMucherino, A
dc.creatorMaculan, N
dc.date2011
dc.dateJAN
dc.date2014-07-30T14:03:40Z
dc.date2015-11-26T16:45:02Z
dc.date2014-07-30T14:03:40Z
dc.date2015-11-26T16:45:02Z
dc.date.accessioned2018-03-28T23:30:34Z
dc.date.available2018-03-28T23:30:34Z
dc.identifierInternational Transactions In Operational Research. Wiley-blackwell, v. 18, n. 1, n. 33, n. 51, 2011.
dc.identifier0969-6016
dc.identifierWOS:000294307600002
dc.identifier10.1111/j.1475-3995.2009.00757.x
dc.identifierhttp://www.repositorio.unicamp.br/jspui/handle/REPOSIP/57756
dc.identifierhttp://repositorio.unicamp.br/jspui/handle/REPOSIP/57756
dc.identifier.urihttp://repositorioslatinoamericanos.uchile.cl/handle/2250/1274103
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionDistance 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.
dc.description18
dc.description1
dc.description33
dc.description51
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.descriptionFundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)
dc.descriptionConselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)
dc.languageen
dc.publisherWiley-blackwell
dc.publisherMalden
dc.publisherEUA
dc.relationInternational Transactions In Operational Research
dc.relationInt. Trans. Oper. Res.
dc.rightsfechado
dc.rightshttp://olabout.wiley.com/WileyCDA/Section/id-406071.html
dc.sourceWeb of Science
dc.subjectdistance geometry
dc.subjectprotein conformation
dc.subjectoptimization
dc.subjectDiffusion Equation Method
dc.subjectVariable Neighborhood Search
dc.subjectGlobal Optimization
dc.subjectBuildup Algorithm
dc.subjectAtomic Distances
dc.subjectContinuation
dc.subjectPerformance
dc.subjectClusters
dc.subjectMinlps
dc.titleMolecular distance geometry methods: from continuous to discrete
dc.typeArtículos de revistas


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