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Visualization of Large Molecular Trajectories
ViRVIG Group, UPC Barcelona, Barcelona, Spain.
Visual Computing Group, U. Ulm, Ulm, Germany.
Visual Computing Group, U. Ulm, Ulm, Germany.ORCID-id: 0000-0002-7857-5512
Masaryk University, Brno, Czech Republic.
Vise andre og tillknytning
2019 (engelsk)Inngår i: IEEE Transactions on Visualization and Computer Graphics, ISSN 1077-2626, E-ISSN 1941-0506, Vol. 25, nr 1, s. 987-996Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

The analysis of protein-ligand interactions is a time-intensive task. Researchers have to analyze multiple physico-chemical properties of the protein at once and combine them to derive conclusions about the protein-ligand interplay. Typically, several charts are inspected, and 3D animations can be played side-by-side to obtain a deeper understanding of the data. With the advances in simulation techniques, larger and larger datasets are available, with up to hundreds of thousands of steps. Unfortunately, such large trajectories are very difficult to investigate with traditional approaches. Therefore, the need for special tools that facilitate inspection of these large trajectories becomes substantial. In this paper, we present a novel system for visual exploration of very large trajectories in an interactive and user-friendly way. Several visualization motifs are automatically derived from the data to give the user the information about interactions between protein and ligand. Our system offers specialized widgets to ease and accelerate data inspection and navigation to interesting parts of the simulation. The system is suitable also for simulations where multiple ligands are involved. We have tested the usefulness of our tool on a set of datasets obtained from protein engineers, and we describe the expert feedback.

sted, utgiver, år, opplag, sider
Institute of Electrical and Electronics Engineers (IEEE), 2019. Vol. 25, nr 1, s. 987-996
Emneord [en]
Molecular visualization, simulation inspection, long trajectories
HSV kategori
Identifikatorer
URN: urn:nbn:se:liu:diva-152557DOI: 10.1109/TVCG.2018.2864851PubMedID: 30207955Scopus ID: 2-s2.0-85053116654OAI: oai:DiVA.org:liu-152557DiVA, id: diva2:1261287
Tilgjengelig fra: 2018-11-06 Laget: 2018-11-06 Sist oppdatert: 2024-08-22bibliografisk kontrollert

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