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dc.contributor.authorFurmanová, Katarína
dc.contributor.authorJurčík, Adam
dc.contributor.authorKozlíková, Barbora
dc.contributor.authorHauser, Helwig
dc.contributor.authorByska, Jan
dc.date.accessioned2020-12-23T09:51:09Z
dc.date.available2020-12-23T09:51:09Z
dc.date.created2020-03-02T19:42:13Z
dc.date.issued2020
dc.PublishedIEEE Transactions on Visualization and Computer Graphics. 2020, 26(1), 843 - 852en_US
dc.identifier.issn1077-2626
dc.identifier.urihttps://hdl.handle.net/11250/2720908
dc.description.abstractWhen studying multi-body protein complexes, biochemists use computational tools that can suggest hundreds or thousands of their possible spatial configurations. However, it is not feasible to experimentally verify more than only a very small subset of them. In this paper, we propose a novel multiscale visual drilldown approach that was designed in tight collaboration with proteomic experts, enabling a systematic exploration of the configuration space. Our approach takes advantage of the hierarchical structure of the data - from the whole ensemble of protein complex configurations to the individual configurations, their contact interfaces, and the interacting amino acids. Our new solution is based on interactively linked 2D and 3D views for individual hierarchy levels. At each level, we offer a set of selection and filtering operations that enable the user to narrow down the number of configurations that need to be manually scrutinized. Furthermore, we offer a dedicated filter interface, which provides the users with an overview of the applied filtering operations and enables them to examine their impact on the explored ensemble. This way, we maintain the history of the exploration process and thus enable the user to return to an earlier point of the exploration. We demonstrate the effectiveness of our approach on two case studies conducted by collaborating proteomic experts.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.titleMultiscale Visual Drilldown for the Analysis of Large Ensembles of Multi-Body Protein Complexesen_US
dc.typeJournal articleen_US
dc.typePeer revieweden_US
dc.description.versionacceptedVersionen_US
dc.rights.holderCopyright 2019 IEEE. All rights reserveden_US
cristin.ispublishedtrue
cristin.fulltextpostprint
cristin.qualitycode2
dc.identifier.doihttps://doi.org/10.1109/TVCG.2019.2934333
dc.identifier.cristin1799088
dc.source.journalIEEE Transactions on Visualization and Computer Graphicsen_US
dc.source.4026en_US
dc.source.141en_US
dc.source.pagenumber843 - 852en_US


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