Idare2—simultaneous visualisation of multiomics data in cytoscape

Detalhes bibliográficos
Autor(a) principal: Pfau, T
Data de Publicação: 2021
Outros Autores: Galhardo, M, Lin, J, Sauter, T
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://hdl.handle.net/10216/152535
Resumo: 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.
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spelling Idare2—simultaneous visualisation of multiomics data in cytoscapeData visualisationMetabolic networksNetwork structureVisual 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.MDPI20212021-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10216/152535eng2218-198910.3390/metabo11050300Pfau, TGalhardo, MLin, JSauter, Tinfo:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-29T14:00:00Zoai:repositorio-aberto.up.pt:10216/152535Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T23:52:03.708588Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Idare2—simultaneous visualisation of multiomics data in cytoscape
title Idare2—simultaneous visualisation of multiomics data in cytoscape
spellingShingle Idare2—simultaneous visualisation of multiomics data in cytoscape
Pfau, T
Data visualisation
Metabolic networks
Network structure
title_short Idare2—simultaneous visualisation of multiomics data in cytoscape
title_full Idare2—simultaneous visualisation of multiomics data in cytoscape
title_fullStr Idare2—simultaneous visualisation of multiomics data in cytoscape
title_full_unstemmed Idare2—simultaneous visualisation of multiomics data in cytoscape
title_sort Idare2—simultaneous visualisation of multiomics data in cytoscape
author Pfau, T
author_facet Pfau, T
Galhardo, M
Lin, J
Sauter, T
author_role author
author2 Galhardo, M
Lin, J
Sauter, T
author2_role author
author
author
dc.contributor.author.fl_str_mv Pfau, T
Galhardo, M
Lin, J
Sauter, T
dc.subject.por.fl_str_mv Data visualisation
Metabolic networks
Network structure
topic Data visualisation
Metabolic networks
Network structure
description 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.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021-01-01T00:00:00Z
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url https://hdl.handle.net/10216/152535
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2218-1989
10.3390/metabo11050300
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dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
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