Spatiotemporal multiscale molecular cavity visualization and visual analysis

Guo, Dongliang; Han, Dongxue; Xu, Ximing; Kang, Young Jin; Nie, Junlan

doi:10.1007/s12650-020-00646-x

Cited by 6 publications

(3 citation statements)

References 29 publications

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“…This permits the identification of a concise yet significant set of normal modes that can be thoroughly examined. In a study by ( Guo et al, 2020 ), a series of scales and visualizations of cavities is constructed, incorporating temporal and spatial perspectives to empower domain experts to manage their work at any level of semantic abstraction. These scales illustrate the chemical and structural properties of cavities, ranging from an entire protein to a cavity at a specific time in both temporal and spatial dimensions.…”

Section: General Considerations On Visualization Of Complex Molecular...mentioning

confidence: 99%

From complex data to clear insights: visualizing molecular dynamics trajectories

Belghit,

Spivak,

Dauchez

et al. 2024

Front. Bioinform.

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Advances in simulations, combined with technological developments in high-performance computing, have made it possible to produce a physically accurate dynamic representation of complex biological systems involving millions to billions of atoms over increasingly long simulation times. The analysis of these computed simulations is crucial, involving the interpretation of structural and dynamic data to gain insights into the underlying biological processes. However, this analysis becomes increasingly challenging due to the complexity of the generated systems with a large number of individual runs, ranging from hundreds to thousands of trajectories. This massive increase in raw simulation data creates additional processing and visualization challenges. Effective visualization techniques play a vital role in facilitating the analysis and interpretation of molecular dynamics simulations. In this paper, we focus mainly on the techniques and tools that can be used for visualization of molecular dynamics simulations, among which we highlight the few approaches used specifically for this purpose, discussing their advantages and limitations, and addressing the future challenges of molecular dynamics visualization.

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Section: General Considerations On Visualization Of Complex Molecular...mentioning

confidence: 99%

From complex data to clear insights: visualizing molecular dynamics trajectories

Belghit,

Spivak,

Dauchez

et al. 2024

Front. Bioinform.

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“…Visual analysis methods include aggregating a molecular dynamics time sequence to a single contour plot [BLG*15]. Heatmaps to show variation in tunnel properties, such as tunnel centerline length, amino acid composition, and bottleneck size, can also be paired with direct visualization of a molecule [BJG*15; GHX*20], as shown in Fig. 7.…”

Section: Molecular Functionmentioning

confidence: 99%

Trends & Opportunities in Visualization for Physiology: A Multiscale Overview

Garrison

Kolesar²,

Viola

et al. 2022

Computer Graphics Forum

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Combining elements of biology, chemistry, physics, and medicine, the science of human physiology is complex and multifaceted. In this report, we offer a broad and multiscale perspective on key developments and challenges in visualization for physiology. Our literature search process combined standard methods with a state-of-the-art visual analysis search tool to identify surveys and representative individual approaches for physiology. Our resulting taxonomy sorts literature on two levels. The first level categorizes literature according to organizational complexity and ranges from molecule to organ. A second level identifies any of three high-level visualization tasks within a given work: exploration, analysis, and communication. The findings of this report may be used by visualization researchers to understand the overarching trends, challenges, and opportunities in visualization for physiology and to provide a foundation for discussion and future research directions in this area. CCS Concepts• Applied computing → Life and medical sciences; • Human-centered computing → Visualization;

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“…如图 10 所示, CAVER Analyst [8] 针对 CAVER 空腔计算结果设计了基于长图 10 CAVER Analyst 空腔分析工具 [8] 计算机辅助设计与图形学学报第 33 卷宽图的空腔形状与内壁氨基酸关联的可视分析方法 [60] 、基于热力图和径向图的空腔瓶颈可视分析方法 [8] . 考虑空腔数据的时空特性, Guo 等 [61] 维特性的洞察 [68] .…”

Section: 研究人员针对原动态空腔计算分析需求开发unclassified