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dc.contributor.authorWu, Hsiang-Yun
dc.contributor.authorNöllenburg, Martin
dc.contributor.authorSousa, Filipa L.
dc.contributor.authorViola, Ivan
dc.date.accessioned2020-08-17T07:55:04Z
dc.date.available2020-08-17T07:55:04Z
dc.date.issued2019
dc.identifier.citationHsiang-Yun Wu, Nรถllenburg Martin, Sousa, F., & Viola, I. (2019). Metabopolis: scalable network layout for biological pathway diagrams in urban map style. Figshare. https://doi.org/10.6084/M9.FIGSHARE.C.4473824.V1
dc.identifier.doi10.6084/m9.figshare.c.4473824.v1
dc.identifier.urihttp://hdl.handle.net/10754/664627
dc.description.abstractAbstract Background Biological pathways represent chains of molecular interactions in biological systems that jointly form complex dynamic networks. The network structure changes from the significance of biological experiments and layout algorithms often sacrifice low-level details to maintain high-level information, which complicates the entire image to large biochemical systems such as human metabolic pathways. Results Our work is inspired by concepts from urban planning since we create a visual hierarchy of biological pathways, which is analogous to city blocks and grid-like road networks in an urban area. We automatize the manual drawing process of biologists by first partitioning the map domain into multiple sub-blocks, and then building the corresponding pathways by routing edges schematically, to maintain the global and local context simultaneously. Our system incorporates constrained floor-planning and network-flow algorithms to optimize the layout of sub-blocks and to distribute the edge density along the map domain. We have developed the approach in close collaboration with domain experts and present their feedback on the pathway diagrams based on selected use cases. Conclusions We present a new approach for computing biological pathway maps that untangles visual clutter by decomposing large networks into semantic sub-networks and bundling long edges to create space for presenting relationships systematically.
dc.publisherfigshare
dc.subjectMedicine
dc.subjectGenetics
dc.subject69999 Biological Sciences not elsewhere classified
dc.subject80699 Information Systems not elsewhere classified
dc.subjectCancer
dc.subjectPlant Biology
dc.subjectComputational Biology
dc.titleMetabopolis: scalable network layout for biological pathway diagrams in urban map style
dc.typeDataset
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentComputer Science Program
dc.contributor.departmentVisual Computing Center (VCC)
dc.contributor.institutionResearch Division of Computer Graphics, Institute of Visual Computing and Human- Centered Technology, TU Wien, Vienna, Austria.
dc.contributor.institutionAlgorithms and Complexity Group, Institute of Logic and Computation, TU Wien, Vienna, Austria.
dc.contributor.institutionArchaea Biology and Ecogenomics Division, Department of Ecogenomics and Systems Biology, University of Vienna, Vienna, Austria.
kaust.personViola, Ivan
dc.relation.issupplementtoDOI:10.1186/s12859-019-2779-4
display.relations<b> Is Supplement To:</b><br/> <ul> <li><i>[Article]</i> <br/> Wu H-Y, Nöllenburg M, Sousa FL, Viola I (2019) Metabopolis: scalable network layout for biological pathway diagrams in urban map style. BMC Bioinformatics 20. Available: http://dx.doi.org/10.1186/s12859-019-2779-4.. DOI: <a href="https://doi.org/10.1186/s12859-019-2779-4" >10.1186/s12859-019-2779-4</a> HANDLE: <a href="http://hdl.handle.net/10754/631962">10754/631962</a></li></ul>


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