Visualization of Protein Dynamics and Systems Biology

Simulations are a key to new insights into protein and systems biology research. New visualization techniques can enable the complex data to be collected.

Molecular dynamics simulations play a major role in biology, pharmaceutcal and medical research. In particular, the analysis of protein properties in different solvents is of interest for many processes. Simulations produce large, time-dependent data sets – so-called trajectories. The visualisation of these trajectories enables the interactive investigation of the simulated properties. Furthermore, the automated extraction of freatures from the raw data and fitting of the visualisations of these features are important. Here, the abstract illustration of solvent properties plays a major role. In order to ensure an interactive analysis and high-quality visualisations, parallel algorithms are being developed. These algorithms take advantage of the features of current multi-core CPUs and programmable GPUs.

In systems biology, correlations play an important role, and visualisations are a great way to make these visible. Hence, the focus of this work lies in the visualisation and interactive exploration of data from this application area. The data to be visualised will be generated by in-silico simulations. Special emphasis is placed on the development of methods, which are carried out on graphic processing units (GPUs). The parallel architecture of GPUs is of interest, because it has the potential to allow high speed-ups of computations.

The aim of this work is to develop a mesoscopic simulation of selected intra-cellular and extra-cellular processes and visualisations which are able to represent the simulation results in meaningful ways. In particular, cellular signal transduction processes will be studied.

Signal concentration of a virtual cell
Microscopic-like image for comparison with wet lab experiment



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