TIMELINE: TRAJECTORY ANALYSIS AND EVENT IDENTIFICATION IN VMD

这个子项目是许多研究子项目中的一个 由NIH/NCRR资助的中心赠款提供的资源。子项目和 研究者（PI）可能从另一个NIH来源获得了主要资金， 因此可以在其他CRISP条目中表示。所列机构为 研究中心，而研究中心不一定是研究者所在的机构。 分析MD轨迹的过程的一个关键部分是识别重要事件。传统上，这需要科学家花费许多时间来检查动画结构，检查大型模拟系统的不同区域，并计算适当的几何，统计和其他属性。更有效地利用科学家的时间是使用“全轨迹”视图，通过对轨迹的每一帧以及整个模拟结构的每个小组件进行分析计算而产生  例如，计算蛋白质的每个残基的二级结构，以及轨迹的每一帧。由此产生的2D图可以快速识别整个轨迹中发生的事件。随着千万亿次计算的发展，这种分析越来越有必要：随着系统规模、时间尺度和轨迹计数的增长，手动查看动画结构所需的时间变得不切实际，而评估静态全轨迹图所需的时间保持不变。

This subproject is one of many research subprojects utilizing the resources provided by a Center grant funded by NIH/NCRR. The subproject and investigator (PI) may have received primary funding from another NIH source, and thus could be represented in other CRISP entries. The institution listed is for the Center, which is not necessarily the institution for the investigator. A key part of the process of analyzing an MD trajectory is identifying importantevents. This traditionally requires a scientist to spend many hours reviewing animatedstructures, examining different regions of a large simulated system, andcalculating appropriate geometric, statistical, and other properties. A more productiveuse of a scientist's time is to use a "whole-trajectory" view, produced byperforming analysis calculations for every frame of a trajectory, and for each smallcomponent of the entire simulated structure  for example, calculating the secondarystructure of every residue of a protein, and for every frame of a trajectory. The 2Dplot that results allows quick identification of events that take place throughout thetrajectory. With the move to petascale computation, such analysis is increasinglynecessary: as system sizes, time scales, and trajectory counts grow, the time requiredto manually review animated structures becomes impractical, while the timerequired to asses a static whole-trajectory plot remains the same.