{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,24]],"date-time":"2026-02-24T15:21:55Z","timestamp":1771946515780,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T00:00:00Z","timestamp":1620259200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Metabolites"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/metabo11050300","type":"journal-article","created":{"date-parts":[[2021,5,6]],"date-time":"2021-05-06T11:10:27Z","timestamp":1620299427000},"page":"300","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["IDARE2\u2014Simultaneous Visualisation of Multiomics Data in Cytoscape"],"prefix":"10.3390","volume":"11","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5048-2923","authenticated-orcid":false,"given":"Thomas","family":"Pfau","sequence":"first","affiliation":[{"name":"Department of Life Sciences and Medicine, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8911-1660","authenticated-orcid":false,"given":"Mafalda","family":"Galhardo","sequence":"additional","affiliation":[{"name":"Department of Life Sciences and Medicine, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg"},{"name":"VDR Lab, Institute for Research and Innovation in Health (i3S), University of Porto, 4200-135 Porto, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9928-1663","authenticated-orcid":false,"given":"Jake","family":"Lin","sequence":"additional","affiliation":[{"name":"Statistical and Population Genetics, Institute for Molecular Medicine Finland, University of Helsinki, 00100 Helsinki, Finland"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8225-2954","authenticated-orcid":false,"given":"Thomas","family":"Sauter","sequence":"additional","affiliation":[{"name":"Department of Life Sciences and Medicine, University of Luxembourg, 4365 Esch-sur-Alzette, Luxembourg"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,6]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"S56","DOI":"10.1038\/nmeth.1436","article-title":"Visualization of omics data for systems biology","volume":"7","author":"Gehlenborg","year":"2010","journal-title":"Nat. Methods"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1093\/bioinformatics\/btq594","article-title":"Paintomics: A web based tool for the joint visualization of transcriptomics and metabolomics data","volume":"27","author":"Dopazo","year":"2011","journal-title":"Bioinformatics"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"W503","DOI":"10.1093\/nar\/gky466","article-title":"PaintOmics 3: A web resource for the pathway analysis and visualization of multi-omics data","volume":"46","author":"Tarazona","year":"2018","journal-title":"Nucleic Acids Res."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Gerasch, A., Faber, D., K\u00fcntzer, J., Niermann, P., Kohlbacher, O., Lenhof, H.P., and Kaufmann, M. (2014). BiNA: A visual analytics tool for biological network data. PLoS ONE, 9.","DOI":"10.1371\/journal.pone.0087397"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1186\/s13062-016-0112-y","article-title":"MONGKIE: An integrated tool for network analysis and visualization for multi-omics data","volume":"11","author":"Jang","year":"2016","journal-title":"Biol. Direct."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Koblitz, J., Schomburg, D., and Neumann-Schaal, M. (2020). MetaboMAPS: Pathway sharing and multi-omics data visualization in metabolic context [version 2; peer review: 2 approved]. F1000Research, 9.","DOI":"10.12688\/f1000research.23427.2"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"2616","DOI":"10.1093\/bioinformatics\/btz927","article-title":"SAMMI: A semi-automated tool for the visualization of metabolic networks","volume":"36","author":"Schultz","year":"2019","journal-title":"Bioinformatics"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1371\/journal.pcbi.1004321","article-title":"Escher: A Web Application for Building, Sharing, and Embedding Data-Rich Visualizations of Biological Pathways","volume":"11","author":"King","year":"2015","journal-title":"PLoS Comput. Biol."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1093\/bib\/bbz104","article-title":"Pathway Tools version 23.0 update: Software for pathway\/genome informatics and systems biology","volume":"22","author":"Karp","year":"2019","journal-title":"Briefings Bioinform."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"W427","DOI":"10.1093\/nar\/gkaa409","article-title":"Fluxer: A web application to compute, analyze and visualize genome-scale metabolic flux networks","volume":"48","author":"Hari","year":"2020","journal-title":"Nucleic Acids Res."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1002\/cite.201200234","article-title":"Omix: A Visualization Tool for Metabolic Networks with Highest Usability and Customizability in Focus","volume":"85","author":"Droste","year":"2013","journal-title":"Chem. Ing. Tech."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2498","DOI":"10.1101\/gr.1239303","article-title":"Cytoscape: A software environment for integrated models of biomolecular interaction networks","volume":"13","author":"Shannon","year":"2003","journal-title":"Genome Res."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"1069","DOI":"10.1038\/nmeth.2212","article-title":"A travel guide to Cytoscape plugins","volume":"9","author":"Saito","year":"2012","journal-title":"Nat. Methods"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1093\/bioinformatics\/btr661","article-title":"Metscape 2 bioinformatics tool for the analysis and visualization of metabolomics and gene expression data","volume":"28","author":"Karnovsky","year":"2012","journal-title":"Bioinformatics"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"147","DOI":"10.12688\/f1000research.4460.1","article-title":"enhancedGraphics: A Cytoscape app for enhanced node graphics","volume":"3","author":"Morris","year":"2014","journal-title":"F1000Res"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"D199","DOI":"10.1093\/nar\/gkt1076","article-title":"Data, information, knowledge and principle: Back to metabolism in KEGG","volume":"42","author":"Kanehisa","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"D459","DOI":"10.1093\/nar\/gkt1103","article-title":"The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of Pathway\/Genome Databases","volume":"42","author":"Caspi","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1040","DOI":"10.1093\/bioinformatics\/btm057","article-title":"Cerebral: A Cytoscape plugin for layout of and interaction with biological networks using subcellular localization annotation","volume":"23","author":"Barsky","year":"2007","journal-title":"Bioinformatics"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1474","DOI":"10.1093\/nar\/gkt989","article-title":"Integrated analysis of transcript-level regulation of metabolism reveals disease-relevant nodes of the human metabolic network","volume":"42","author":"Galhardo","year":"2014","journal-title":"Nucleic Acids Res."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1002\/bit.22844","article-title":"Systematizing the generation of missing metabolic knowledge","volume":"107","author":"Orth","year":"2010","journal-title":"Biotechnol. Bioeng."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"2402","DOI":"10.1093\/bioinformatics\/bts432","article-title":"CySBML: A Cytoscape plugin for SBML","volume":"28","year":"2012","journal-title":"Bioinformatics"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"544","DOI":"10.1016\/j.bpj.2010.12.3707","article-title":"Elimination of thermodynamically infeasible loops in steady-state metabolic models","volume":"100","author":"Schellenberger","year":"2011","journal-title":"Biophys. J."},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Pfau, T., Pacheco, M.P., and Sauter, T. (2015). Towards improved genome-scale metabolic network reconstructions: Unification, transcript specificity and beyond. Brief Bioinform., 17.","DOI":"10.1093\/bib\/bbv100"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"3383","DOI":"10.1093\/bioinformatics\/btv341","article-title":"JSBML 1.0: Providing a smorgasbord of options to encode systems biology models","volume":"31","author":"Rodriguez","year":"2015","journal-title":"Bioinformatics"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1093\/bib\/bbp056","article-title":"BioModels.net Web Services, a free and integrated toolkit for computational modelling software","volume":"11","author":"Li","year":"2010","journal-title":"Brief Bioinform."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Orth, J.D., Fleming, R.M.T., and Palsson, B.O. (2010). Reconstruction and Use of Microbial Metabolic Networks: The Core E. coli Metabolic Model as an Educational Guide. EcoSal Plus.","DOI":"10.1128\/ecosalplus.10.2.1"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"103","DOI":"10.3389\/fmicb.2015.00103","article-title":"Characterization of the E. coli proteome and its modifications during growth and ethanol stress","volume":"6","author":"Soufi","year":"2015","journal-title":"Front. Microbiol."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Horinouchi, T., Tamaoka, K., Furusawa, C., Ono, N., Suzuki, S., Hirasawa, T., Yomo, T., and Shimizu, H. (2010). Transcriptome analysis of parallel-evolved Escherichia coli strains under ethanol stress. BMC Genom., 11.","DOI":"10.1186\/1471-2164-11-579"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"5302","DOI":"10.1021\/pr400640u","article-title":"Global Metabolomic and Network analysis of E. coli Responses to Exogenous Biofuels","volume":"12","author":"Wang","year":"2013","journal-title":"J. Proteome Res."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1038\/msb.2010.33","article-title":"Regulatory and metabolic rewiring during laboratory evolution of ethanol tolerance in E. coli","volume":"6","author":"Goodarzi","year":"2010","journal-title":"Mol. Syst. Biol."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"348","DOI":"10.1089\/zeb.2018.1712","article-title":"Predicting Metabolism from Gene Expression in an Improved Whole-Genome Metabolic Network Model of Danio rerio","volume":"16","author":"Verbeek","year":"2019","journal-title":"Zebrafish"}],"container-title":["Metabolites"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2218-1989\/11\/5\/300\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:57:34Z","timestamp":1760162254000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2218-1989\/11\/5\/300"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,6]]},"references-count":31,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["metabo11050300"],"URL":"https:\/\/doi.org\/10.3390\/metabo11050300","relation":{},"ISSN":["2218-1989"],"issn-type":[{"value":"2218-1989","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,6]]}}}