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.
Original language | English (US) |
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Pages (from-to) | 4490-4492 |
Number of pages | 3 |
Journal | Bioinformatics |
Volume | 35 |
Issue number | 21 |
DOIs | |
State | Published - Nov 1 2019 |
Funding
This work was supported by the Hungarian National Research, Development and Innovation Office (Grant Nos. NVKP_16-1-2016-0017, B.Á.; KH_17-125570, P.F. and K115378, P.C.) and by the Higher Education Institutional Excellence Programme of the Ministry of Human Capacities in Hungary, within the framework of the Therapeutic Development (P.F.) and Molecular Biology (P.C.) thematic programmes of the Semmelweis University.
ASJC Scopus subject areas
- Statistics and Probability
- Biochemistry
- Molecular Biology
- Computer Science Applications
- Computational Theory and Mathematics
- Computational Mathematics