ProtEGOnist – Exploration of protein-protein interactions using ego-graph networks

Nicolas Brich, Theresa Harbig, Mathias Witte Paz, Simon Tim Hackl, Caroline Jachmann, Marco Schäfer, Michael Krone, Kay Nieselt

Room: 111-112

2023-10-22T22:00:00ZGMT-0600Change your timezone on the schedule page
2023-10-22T22:00:00Z
Exemplar figure, described by caption below
ProtEGOnist focuses on comparing the local protein-protein interaction neighborhoods - called ego-graphs - of proteins of interest. It consists of three views: (1) a network of ego-graphs of the proteins of interest, (2) an ego-graph subnetwork of ego-graphs selected from the overview that provides more details on the ego-graphs and their overlap when decollapsing them, and (3) a radar chart showing the similarity between a selected ego-graph and its neighbor ego-graphs, which are grouped by the function of the central protein using the BRITE hierarchy. All views are linked and provide details on demand.
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Abstract

The complexity of protein-protein interaction (PPI) networks often leads to visual clutter and limited interpretability. To overcome these problems, we present ProtEGOnist, a novel, interactive visualization approach designed to explore PPI networks with a focus on drug-protein associations. ProtEGOnist addresses the challenges by introducing the concept of ego-graphs to represent local PPI neighborhoods around proteins of interest. These ego-graphs are aggregated into an ego-graph network, where edges between ego-graphs encoded their similarity using the Jaccard index. Our proposed visualization design offers an overview of drug-associated proteins, radar charts to compare protein functions, and detailed ego-graph subnetworks for interactive exploration. Our aim was to reduce visual complexity while enabling detailed exploration, facilitating the discovery of meaningful patterns in PPI networks. A web-based prototype of ProtEGOnist is available for interactive use.