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dc.contributor.authorJurcik, Adam
dc.contributor.authorFurmanova, Katarina
dc.contributor.authorByska, Jan
dc.contributor.authorVonasek, Vojtech
dc.contributor.authorVavra, Ondrej
dc.contributor.authorUlbrich, Pavol
dc.contributor.authorHauser, Helwig
dc.contributor.authorKozlikova, Barbora
dc.date.accessioned2020-12-23T10:01:54Z
dc.date.available2020-12-23T10:01:54Z
dc.date.created2019-11-07T19:42:49Z
dc.date.issued2019
dc.PublishedIEEE Pacific Visualization Symposium. 2019, 2019-April 212-221.en_US
dc.identifier.issn2165-8765
dc.identifier.urihttps://hdl.handle.net/11250/2720912
dc.description.abstractIn many cases, protein reactions with other small molecules (ligands) occur in a deeply buried active site. When studying these types of reactions, it is crucial for biochemists to examine trajectories of ligand motion. These trajectories are predicted with in-silico methods that produce large ensembles of possible trajectories. In this paper, we propose a novel approach to the interactive visual exploration and analysis of large sets of ligand trajectories, enabling the domain experts to understand protein function based on the trajectory properties. The proposed solution is composed of multiple linked 2D and 3D views, enabling the interactive exploration and filtering of trajectories in an informed way. In the workflow, we focus on the practical aspects of the interactive visual analysis specific to ligand trajectories. We adapt the small multiples principle to resolve an overly large number of trajectories into smaller chunks that are easier to analyze. We describe how drill-down techniques can be used to create and store selections of the trajectories with desired properties, enabling the comparison of multiple datasets. In appropriately designed 2D and 3D views, biochemists can either observe individual trajectories or choose to aggregate the information into a functional boxplot or density visualization. Our solution is based on a tight collaboration with the domain experts, aiming to address their needs as much as possible. The usefulness of our novel approach is demonstrated by two case studies, conducted by the collaborating protein engineers.en_US
dc.language.isoengen_US
dc.publisherIEEEen_US
dc.titleVisual Analysis of Ligand Trajectories in Molecular Dynamicsen_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.qualitycode1
dc.identifier.doi10.1109/PacificVis.2019.00032
dc.identifier.cristin1745105
dc.source.journalIEEE Pacific Visualization Symposiumen_US
dc.source.402019-Aprilen_US
dc.source.pagenumber212-221en_US


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