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dc.contributor.authorAlbrecht, A.
dc.contributor.authorSkaliotis, A.
dc.contributor.authorSteinhofel, K.
dc.identifier.citationAlbrecht , A , Skaliotis , A & Steinhofel , K 2008 , ' Stochastic protein folding simulation in the three-dimensional HP-model ' , Computational Biology and Chemistry , vol. 32 , no. 4 , pp. 248-255 .
dc.identifier.otherPURE: 83935
dc.identifier.otherPURE UUID: b0de66e1-1b89-4816-9e05-7aaced832871
dc.identifier.otherdspace: 2299/5928
dc.identifier.otherScopus: 45549094900
dc.descriptionOriginal article can be found at : Copyright Elsevier [Full text of this article is not available in the UHRA]
dc.description.abstractWe present results from three-dimensional protein folding simulations in the HP-model on ten benchmark problems. The simulations are executed by a simulated annealing-based algorithm with a time-dependent cooling schedule. The neighbourhood relation is determined by the pull-move set. The results provide experimental evidence that the maximum depth D of local minima of the underlying energy landscape can be upper bounded by D<n2/3. The local search procedure employs the stopping criterion (m/δ)D/γ, where m is an estimation of the average number of neighbouring conformations, γ relates to the mean of non-zero differences of the objective function for neighbouring conformations, and 1−δ is the confidence that a minimum conformation has been found. The bound complies with the results obtained for the ten benchmark problems.en
dc.relation.ispartofComputational Biology and Chemistry
dc.subjectprotein folding
dc.subjectlandscape analysis
dc.subjectstochastic local search
dc.subjectsimulated annealing
dc.titleStochastic protein folding simulation in the three-dimensional HP-modelen
dc.contributor.institutionSchool of Computer Science
dc.description.statusPeer reviewed
dc.relation.schoolSchool of Computer Science
rioxxterms.typeJournal Article/Review

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