Reference : IDARE2-Simultaneous Visualisation of Multiomics Data in Cytoscape.
Scientific journals : Article
Life sciences : Multidisciplinary, general & others
http://hdl.handle.net/10993/47497
IDARE2-Simultaneous Visualisation of Multiomics Data in Cytoscape.
English
Pfau, Thomas [> >]
Galhardo, Mafalda [> >]
Lin, Jake [> >]
Sauter, Thomas mailto [University of Luxembourg > Faculty of Science, Technology and Medicine (FSTM) > Department of Life Sciences and Medicine (DLSM)]
2021
Metabolites
11
5
Yes (verified by ORBilu)
International
2218-1989
2218-1989
[en] data visualisation ; metabolic networks ; network structure
[en] Visual integration of experimental data in metabolic networks is an important step to understanding their meaning. As genome-scale metabolic networks reach several thousand reactions, the task becomes more difficult and less revealing. While databases like KEGG and BioCyc provide curated pathways that allow a navigation of the metabolic landscape of an organism, it is rather laborious to map data directly onto those pathways. There are programs available using these kind of databases as a source for visualization; however, these programs are then restricted to the pathways available in the database. Here, we present IDARE2 a cytoscape plugin that allows the visualization of multiomics data in cytoscape in a user-friendly way. It further provides tools to disentangle highly connected network structures based on common properties of nodes and retains structural links between the generated subnetworks, offering a straightforward way to traverse the splitted network. The tool is extensible, allowing the implementation of specialised representations and data format parsers. We present the automated reproduction of the original IDARE nodes using our tool and show examples of other data being mapped on a network of E. coli. The extensibility is demonstrated with two plugins that are available on github. IDARE2 provides an intuitive way to visualise data from multiple sources and allows one to disentangle the often complex network structure in large networks using predefined properties of the network nodes.
Researchers ; Professionals ; Students
http://hdl.handle.net/10993/47497

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