2019
Visual Analysis of Ligand Trajectories in Molecular Dynamics
JURČÍK, Adam, Katarína FURMANOVÁ, Jan BYŠKA, Vojtěch VONÁSEK, Ondřej VÁVRA et. al.Základní údaje
Originální název
Visual Analysis of Ligand Trajectories in Molecular Dynamics
Autoři
JURČÍK, Adam (203 Česká republika, domácí), Katarína FURMANOVÁ (703 Slovensko, domácí), Jan BYŠKA (203 Česká republika, domácí), Vojtěch VONÁSEK (203 Česká republika), Ondřej VÁVRA (203 Česká republika, domácí), Pavol ULBRICH (703 Slovensko, domácí), Helwig HAUSER a Barbora KOZLÍKOVÁ (203 Česká republika, garant, domácí)
Vydání
Bangkok, Thailand, IEEE Pacific Visualization Symposium 2019, od s. 212-221, 10 s. 2019
Nakladatel
IEEE
Další údaje
Jazyk
angličtina
Typ výsledku
Stať ve sborníku
Obor
10201 Computer sciences, information science, bioinformatics
Stát vydavatele
Thajsko
Utajení
není předmětem státního či obchodního tajemství
Forma vydání
elektronická verze "online"
Kód RIV
RIV/00216224:14330/19:00107231
Organizační jednotka
Fakulta informatiky
ISBN
978-1-5386-9226-4
ISSN
UT WoS
000502097000020
Klíčová slova anglicky
trajectory;ligand;protein;molecular dynamics;visualization;visual analysis
Příznaky
Mezinárodní význam, Recenzováno
Změněno: 27. 4. 2020 22:32, RNDr. Pavel Šmerk, Ph.D.
Anotace
V originále
In 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.
Návaznosti
GA17-07690S, projekt VaV |
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MUNI/A/1040/2018, interní kód MU |
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