Trajectory analysis

Bio3D 1 is an R package that provides interactive tools for the analysis of bimolecular structure, sequence and simulation data. The aim of this document, termed a vignette 2 in R parlance, is to provide a brief task-oriented introduction to basic molecular dynamics trajectory analysis with the Bio3D R package Grant et al. Detailed instructions for obtaining and installing the Bio3D package on various platforms can be found in the Installing Bio3D vignette available online. This particular vignette was generated using Bio3D version 2. Start R, load the Bio3D package and use the command demo "md" to get a quick feel for some of the tasks that we will be introducing in the following sections. Note that you will be prompted to hit the RETURN key at each step of the demo as this will allow you to see the particular functions being called.
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Trajectory Analysis

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Trajectory Analysis

A trajectory describes the course of a measured variable over age or time. Investigators in epidemiology and other fields are often interested not only in the trajectory of variables over time, but also in how covariates may affect their shape. Traditionally, hierarchical modeling and latent curve analysis have been used to measure these relationships, but in recent years, a group-based approach known as group-based trajectory modeling has increased in popularity as an alternative. Whereas hierarchical modeling and latent curve analysis estimate the population average trajectory and use covariates to explain variability about this average, group-based trajectory modeling assumes that the population is composed of distinct groups, each with a different underlying trajectory. It identifies groups of individuals following similar progressions of some phenomenon over time and estimates the effects of covariates not only on trajectory shape, but also group membership.
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The Universe binds together the static topology which atoms, how are they connected, what un-changing properties do the atoms possess such as partial charge , … and the changing coordinate information, which is stored in the trajectory. The standard way to assess each time step or frame in a trajectory is to iterate over the Universe. The time attribute contains the current time step. The Reader only contains information about one time step : imagine a cursor or pointer moving along the trajectory file.
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