A Web-based Visual Analytics Application for Biological Networks

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dc.contributor.authorKrone, Michaelen_US
dc.contributor.authorDräger, Andreasen_US
dc.contributor.authorCobanoglu, Ebruen_US
dc.contributor.authorHarke, Manuel Ottoen_US
dc.contributor.authorHoene, Miriamen_US
dc.contributor.authorWeigert, Coraen_US
dc.contributor.authorLehmann, Raineren_US
dc.contributor.editorByška, Jan and Jänicke, Stefanen_US
dc.date.accessioned2020-05-24T13:49:42Z
dc.date.available2020-05-24T13:49:42Z
dc.date.issued2020
dc.description.abstractModern high-throughput methods enable rapidly obtaining transcriptomics data, which includes information about the expression rate of genes. The expression rates are usually given as fold change, which describes the over- or under-expression of each gene. Each gene can be part of one or more biological pathways. A pathway models the interactions between molecules in an organism that lead to a particular chemical change. Consequently, many applications in medical research need to analyze the impact of gene expression changes on the biological pathways of an organism. It allows concluding diseases or other conditions of the organism. We present a web-based visual analytics application that facilitates exploring the network of biological pathways corresponding to a given set of genes. The network is constructed from pathways derived from an external database. Users can interactively zoom and filter the network and get details on demand. Our application is currently work in progress and is developed in close collaboration with medical researchers. In subsequent steps, we strive to add more features, such as the ability to compare data from different individuals or to visualize time series data. Furthermore, we want to extend our application to visualize not just transcriptomics but multi-omics data.en_US
dc.description.sectionheadersPosters
dc.description.seriesinformationEuroVis 2020 - Posters
dc.identifier.doi10.2312/eurp.20201124
dc.identifier.isbn978-3-03868-105-2
dc.identifier.pages41-43
dc.identifier.urihttps://doi.org/10.2312/eurp.20201124
dc.identifier.urihttps://diglib.eg.org:443/handle/10.2312/eurp20201124
dc.publisherThe Eurographics Associationen_US
dc.rightsAttribution 4.0 International License
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/]
dc.subjectHuman centered computing
dc.subjectVisualization systems and tools
dc.subjectApplied computing
dc.subjectSystems biology
dc.subjectTranscriptomics
dc.titleA Web-based Visual Analytics Application for Biological Networksen_US
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