# The EntOptLayout Cytoscape plug-in for the efficient visualization of   major protein complexes in protein-protein interaction and signalling   networks

**Authors:** Bence Agg, Andrea Csaszar, Mate Szalay-Beko, Daniel V. Veres, Reka, Mizsei, Peter Ferdinandy, Peter Csermely, Istvan A. Kovacs

arXiv: 1904.03910 · 2019-11-04

## TL;DR

The EntOptLayout Cytoscape plug-in offers an efficient method for visualizing major protein complexes within complex biological networks, significantly reducing information loss and improving interpretability over traditional visualization techniques.

## Contribution

This paper introduces a novel Cytoscape plug-in based on network representation theory that enhances visualization of network modules with quality scoring.

## Key findings

- Achieves 3- to 25-fold reduction in information loss compared to conventional methods.
- Effectively visualizes protein complexes in interaction and signaling networks.
- Available as a free, cross-platform tool with tutorials.

## Abstract

Motivation: Network visualizations of complex biological datasets usually result in 'hairball' images, which do not discriminate network modules. Results: We present the EntOptLayout Cytoscape plug-in based on a recently developed network representation theory. The plug-in provides an efficient visualization of network modules, which represent major protein complexes in protein-protein interaction and signalling networks. Importantly, the tool gives a quality score of the network visualization by calculating the information loss between the input data and the visual representation showing a 3- to 25-fold improvement over conventional methods. Availability and implementation: The plug-in (running on Windows, Linux, or Mac OS) and its tutorial (both in written and video forms) can be downloaded freely under the terms of the MIT license from: http://apps.cytoscape.org/apps/entoptlayout. Supplementary data are available at Bioinformatics online. Contact: csermely.peter@med.semmelweis-univ.hu

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Source: https://tomesphere.com/paper/1904.03910