Interactive Visualization of Protein RINs using NetworKit in the Cloud

Abstract

Network analysis has been applied in diverse application domains. We consider an application from protein dynamics, specifically residue interaction networks (RINs). While numerous RIN visualization tools exist, there are no solutions that are both easily programmable and as fast as optimized network analysis toolkits. In this work, we use NetworKit - an established package for network analysis - to build a cloud-based environment that enables domain scientists to run their visualization and analysis workflows on large compute servers, without requiring extensive programming and/or system administration knowledge. To demonstrate the versatility of this approach, we use it to build a custom Jupyter-based widget for RIN visualization. In contrast to existing RIN visualization approaches, our widget can easily be customized through simple modifications of Python code, while both supporting a comprehensive feature set and providing near real-time speed. Due to its integration into Jupyter notebooks, our widget can easily interact with other popular packages of the Python ecosystem to build custom analysis pipelines (e.g., pipelines that feed RIN data into downstream machine learning tasks).