Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Real Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo

Full metadata record
DC Field Value Language
dc.contributor.author전수영-
dc.date.accessioned2021-09-08T22:23:27Z-
dc.date.available2021-09-08T22:23:27Z-
dc.date.created2021-06-17-
dc.date.issued2009-
dc.identifier.issn1225-066X-
dc.identifier.urihttps://scholar.korea.ac.kr/handle/2021.sw.korea/121229-
dc.description.abstractRecently, the general contour Monte Carlo has been proposed by Liang (2004) as a space annealing version(ACMC) for optimization problems. The algorithm can be applied successfully to determine the ground configurations for the prediction of protein folding. In this approach, we use the distances between the consecutive $C_alpha atoms along the peptide chain and the mapping sequences between the 20-letter amino acids and a coarse-grained three-letter code. The algorithm was tested on the real proteins. The comparison showed that the algorithm made a significant improvement over the simulated annealing(SA) and the Metropolis Monte Carlo method in determining the ground configurations.-
dc.languageEnglish-
dc.language.isoen-
dc.publisher한국통계학회-
dc.titleReal Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo-
dc.title.alternativeReal Protein Prediction in an Off-Lattice BLN Model via Annealing Contour Monte Carlo-
dc.typeArticle-
dc.contributor.affiliatedAuthor전수영-
dc.identifier.bibliographicCitation응용통계연구, v.22, no.3, pp.627 - 634-
dc.relation.isPartOf응용통계연구-
dc.citation.title응용통계연구-
dc.citation.volume22-
dc.citation.number3-
dc.citation.startPage627-
dc.citation.endPage634-
dc.type.rimsART-
dc.identifier.kciidART001353949-
dc.description.journalClass2-
dc.description.journalRegisteredClasskci-
dc.subject.keywordAuthorProtein folding-
dc.subject.keywordAuthorannealing contour Monte Carlo-
dc.subject.keywordAuthorsimulated annealing-
dc.subject.keywordAuthorBLN model.-
Files in This Item
There are no files associated with this item.
Appears in
Collections
Graduate School > Department of Applied Statistics > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Altmetrics

Total Views & Downloads

BROWSE