Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization

BYŠKA, Jan, Thomas TRAUTNER, Sérgio Manuel MARQUES, Jiří DAMBORSKÝ, Barbora KOZLÍKOVÁ and Manuela WALDNER. Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization. Computer Graphics Forum. Wiley-Blackwell, 2019, vol. 38, No 3, p. 441-453. ISSN 0167-7055. Available from: https://dx.doi.org/10.1111/cgf.13701.

Basic information

• Original name: Analysis of Long Molecular Dynamics Simulations Using Interactive Focus+Context Visualization
• Authors: BYŠKA, Jan (203 Czech Republic, guarantor, belonging to the institution), Thomas TRAUTNER (40 Austria), Sérgio Manuel MARQUES (620 Portugal, belonging to the institution), Jiří DAMBORSKÝ (203 Czech Republic, belonging to the institution), Barbora KOZLÍKOVÁ (203 Czech Republic, belonging to the institution) and Manuela WALDNER (40 Austria).
• Edition: Computer Graphics Forum, Wiley-Blackwell, 2019, 0167-7055.

Other information

• Original language: English
• Type of outcome: Article in a journal
• Field of Study: 10200 1.2 Computer and information sciences
• Country of publisher: Switzerland
• Confidentiality degree: is not subject to a state or trade secret
• WWW: URL
• Impact factor: Impact factor: 2.116
• RIV identification code: RIV/00216224:14330/19:00107361
• Organization unit: Faculty of Informatics
• Doi: http://dx.doi.org/10.1111/cgf.13701
• UT WoS: 000481468200035
• Keywords in English: Molecular Visualization;Design Studies;Focus + Context Techniques
• Tags: International impact, Reviewed

Abstract

Analyzing molecular dynamics (MD) simulations is a key aspect to understand protein dynamics and function. With increasing computational power, it is now possible to generate very long and complex simulations, which are cumbersome to explore using traditional 3D animations of protein movements. Guided by requirements derived from multiple focus groups with protein engineering experts, we designed and developed a novel interactive visual analysis approach for long and crowded MD simulations. In this approach, we link a dynamic 3D focus+context visualization with a 2D chart of time series data to guide the detection and navigation towards important spatio-temporal events. The 3D visualization renders elements of interest in more detail and increases the temporal resolution dependent on the time series data or the spatial region of interest. In case studies with different MD simulation data sets and research questions, we found that the proposed visual analysis approach facilitates exploratory analysis to generate, confirm, or reject hypotheses about causalities. Finally, we derived design guidelines for interactive visual analysis of complex MD simulation data.

Links

• GC18-18647J, research and development project: Name: Vizuální analýza interakcí proteinů a ligandů (Acronym: PROLINT)

Investor: Czech Science Foundation