Protein Shape Retrieval

dc.contributor.authorSong, Naen_US
dc.contributor.authorCraciun, Danielaen_US
dc.contributor.authorChristoffer, Charles W.en_US
dc.contributor.authorHan, Xusien_US
dc.contributor.authorKihara, Daisukeen_US
dc.contributor.authorLevieux, Guillaumeen_US
dc.contributor.authorMontes, Matthieuen_US
dc.contributor.authorQin, Hongen_US
dc.contributor.authorSahu, Pranjalen_US
dc.contributor.authorTerashi, Genkien_US
dc.contributor.authorLiu, Haiguangen_US
dc.contributor.editorIoannis Pratikakis and Florent Dupont and Maks Ovsjanikoven_US
dc.date.accessioned2017-04-22T17:17:43Z
dc.date.available2017-04-22T17:17:43Z
dc.date.issued2017
dc.description.abstractThe large number of protein structures deposited in the protein database provide an opportunity to examine the structure relations using computational algorithms, which can be used to classify the structures based on shape similarity. In this paper, we report the result of the SHREC 2017 track on shape retrievals from protein database. The goal of this track is to test the performance of the algorithms proposed by participants for the retrieval of bioshape (proteins). The test set is composed of 5,854 abstracted shapes from actual protein structures after removing model redundancy. Ten query shapes were selected from a set of representative molecules that have important biological functions. Six methods from four teams were evaluated and the performance is summarized in this report, in which both the retrieval accuracy and computational speed were compared. The biological relevance of the shape retrieval approaches is discussed. We also discussed the future perspectives of shape retrieval for biological molecular models.en_US
dc.description.sectionheadersSHREC Session II
dc.description.seriesinformationEurographics Workshop on 3D Object Retrieval
dc.identifier.doi10.2312/3dor.20171055
dc.identifier.isbn978-3-03868-030-7
dc.identifier.issn1997-0471
dc.identifier.pages67-74
dc.identifier.urihttps://doi.org/10.2312/3dor.20171055
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/3dor20171055
dc.publisherThe Eurographics Associationen_US
dc.subjectComputing methodologies
dc.subjectShape modeling
dc.subjectComputing methodologies
dc.subjectShape analysis
dc.titleProtein Shape Retrievalen_US
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