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BioNetIllustration

BioNetIllustration: User centric illustrations of biological networks

Total Cost €

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EC-Contrib. €

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Partnership

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Project "BioNetIllustration" data sheet

The following table provides information about the project.

Coordinator
TECHNISCHE UNIVERSITAET WIEN 

Organization address
address: KARLSPLATZ 13
city: WIEN
postcode: 1040
website: www.tuwien.ac.at

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Austria [AT]
 Project website https://www.cg.tuwien.ac.at/research/projects/BioNetIllustration/
 Total cost 166˙156 €
 EC max contribution 166˙156 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2016
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-06-01   to  2019-06-20

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    TECHNISCHE UNIVERSITAET WIEN AT (WIEN) coordinator 166˙156.00

Map

 Project objective

In living systems, one molecule is commonly involved in several distinct physiological functions. The roles of molecules are commonly summarized in pathway diagrams, which, however, are abstract, hierarchically nested and thus is difficult to comprehend especially by non-expert audience. The primary goal of this research in visualization is to intuitively support the comprehensive understanding of relationships among biological networks using interactively computed illustrations. Illustrations, especially in textbooks of biology are carefully designed to clearly present reactions between organs as well as interactions within cells. Automatic generation of illustrative visualizations of biological networks is thus the technical content of this proposal. Automatic generation of hand-drawn illustrations has been a challenging task due to the difficulty of algorithmically describing a human creative process such as evaluating and selecting significant information and composing meaningful explanations in a visually plausible manner. Our high-level idea in BioNetIllustration is to simulate this process by decomposing the entire problem into multiple steps including content-driven layout and illustration design as well as spatio-temporal event transitions across multiple representations. As a pioneer study on illustrations, a new visualization framework for these network illustrations will be developed. This study can be achieved by matching the unique competences of the researcher and the host research group and allows an innovative synthesis to produce hand-drawn like illustrations of biological networks. The project also involves experts from several disciplines including network and medical visualization, data mining, systems biology as well as perceptual psychology. The result will provide a new direction for physiological process analysis and accelerate the knowledge transfer not only within experts but also to the public.

 Publications

year authors and title journal last update
List of publications.
2018 Daniel Archambault, Jessie Kennedy, Tatiana von Landesberger, Mark McCann, Fintan McGee, Benjamin Renoust, Hsiang-Yun Wu
Lost in Translation: Alignment of Mental Representations for Visual Analytics
published pages: , ISSN: , DOI:
Reimagining the Mental Map and Drawing Stability (NII Shonan Meeting Seminar 127) 2020-01-21
2019 David Kouril, Ladislav Cmolik, Barbora Kozlikova, Hslanc-Yun Wu, Graham Johnson, David S. Goodsell, Arthur Olson, M. Eduard Groller, Ivan Viola
Labels on Levels: Labeling of Multi-Scale Multi-Instance and Crowded 3D Biological Environments
published pages: 977-986, ISSN: 1077-2626, DOI: 10.1109/tvcg.2018.2864491
IEEE Transactions on Visualization and Computer Graphics 25/1 2020-01-21
2019 Hsiang-Yun Wu, Benjamin Niedermann, Shigeo Takahashi, Martin Nöllenburg
A Survey on Computing Schematic Network Maps: The Challenge to Interactivity
published pages: , ISSN: , DOI:
The 2nd Schematic Mapping Workshop 2020-01-21
2018 Vahan Yoghourdjian, Daniel Archambault, Stephan Diehl, Tim Dwyer, Karsten Klein, Helen C. Purchase, Hsiang-Yun Wu
Exploring the limits of complexity: A survey of empirical studies on graph visualisation
published pages: 264-282, ISSN: 2468-502X, DOI: 10.1016/j.visinf.2018.12.006
Visual Informatics 2/4 2020-01-21
2019 Hsiang-Yun Wu, Martin No ̈llenburg, Ivan Viola
Graph Models for Biological Pathway Visualization: State of the Art and Future Challenges
published pages: , ISSN: , DOI:
2020-01-21
2019 Kazuyo Mizuno, Hsiang‐Yun Wu, Shigeo Takahashi, Takeo Igarashi
Optimizing Stepwise Animation in Dynamic Set Diagrams
published pages: 13-24, ISSN: 0167-7055, DOI: 10.1111/cgf.13668
Computer Graphics Forum 38/3 2020-01-21
2019 Hsiang-Yun Wu, Martin Nöllenburg, Ivan Viola
A Visual Comparison of Hand-Drawn and Machine-Generated Human Metabolic Pathways
published pages: , ISSN: , DOI:
2020-01-21
2019 Maximillian Sbardellati, Haichao Miao, Hsiang-Yun Wu, Meister Eduard Gröller, Ivan Barisic, Ivan Viola
Interactive Exploded Views for Molecular Structures
published pages: , ISSN: , DOI:
Proceedings of the 9th Eurographics Workshop on Visual Computing for Biology and Medicine 2020-01-21
2018 Radu Jianu, Martin Krzywinski, Luana Micallef, Hsiang-Yun Wu
Mapifying the Genome
published pages: , ISSN: , DOI:
Scalable Set Visualizations (Dagstuhl Seminar 17332) 2020-01-21
2019 Hsiang-Yun Wu, Martin Nöllenburg, Filipa L. Sousa, Ivan Viola
Metabopolis: scalable network layout for biological pathway diagrams in urban map style
published pages: , ISSN: 1471-2105, DOI: 10.1186/s12859-019-2779-4
BMC Bioinformatics 20/1 2020-01-21
2019 Hsiang-Yun Wu, Martin Nöllenburg, Ivan Viola
The Travel of a Metabolite
published pages: , ISSN: , DOI:
PacificVis 2018 Data Story Telling Contest 2020-01-21
2019 Hsiang-Yun Wu, Haichao Miao, Ivan Viola
From Cells to Atoms - Biological Information Visualization (in Chinese)
published pages: , ISSN: , DOI:
2020-01-21
2017 Hsiang-Yun Wu, Shigeo Takahashi, Rie Ishida
Overlap-free labeling of clustered networks based on Voronoi tessellation
published pages: , ISSN: 1045-926X, DOI: 10.1016/j.jvlc.2017.09.008
Journal of Visual Languages & Computing 2020-01-21

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