Analysis of biomolecular simulation data

review

This workshop was held on the 7th July 2006 at the University of Nottingham. The workshop focused on two techniques, Principal Component Analysis (PCA) and 'R' as a platform for biomolecular simulation analysis.

Molecular dynamics simulations can produce huge quantities of data, and nowadays it is common that more time is spent trying to analyse this data than is required to generate it in the first place. For this reason, techniques to aid data analysis and visualisation are of increasing importance for the biomolecular simulation community.

The aim of the workshop was to introduce tools and techniques for the analysis of biomolecular simulation data. There were two sessions comprising of introductory lectures and hands on practicals, given by Charlie Laughton, University of Nottingham (PCA) and Leo Caves, University of York (R).

downloads

Principal Component Analysis
PCA can reduce complex dynamical data to a much simpler and readily visualisable form, but is also a quantitative technique so that questions like ‘is my simulation equilibrated?’, or ‘are the dynamics of my enzyme in the presence of inhibitor A significantly different to how it behaves when bound to inhibitor B?’ can be evaluated rigorously.

All documentation for the PCA part of the course can be downloaded here.

The PCA code and a manual for its use can be downloaded from the software pages of this website.

R as a platform for biomolecular simulation analysis
'R' is a programming language and environment for data manipulation, analysis and graphical display. R offers a flexible and extensible platform for a wide range of multivariate and time-series analyses that are useful for understanding the data from biomolecular simulations.

All documentation for the 'R' part of the course can be downloaded here.

The 'R' program is available to download from http://www.r-project.org

The Bio3D package can be downloaded here.

showcase talk

These two sessions were followed by a showcase talk on the use of BioSimGrid and Python, given by Kaihsu Tai, University of Oxford.

The BioSimGrid presentation can be downloaded here.