ScaleTrotter: Multi-Scale Visualization Of Biological Data.pdf

Halladjian_2020-paper.pdf
Preview of ScaleTrotter: Multi-Scale Visualization of Biological Data
🔗 Source: cg.tuwien.ac.at
📊 Size: 14.28 MB
👤 Author: Sarkis Halladjian, Haichao Miao, David Kouril, M. Eduard Gröller, Ivan Viola, and Tobias Isenberg
⬇️ Downloads: 54

Summary

ScaleTrotter is an interactive visualization framework designed to explore multi-scale biological data, particularly the human genome. It bridges orders of magnitude, from the nucleus (6 µm) to atomic levels (2 nm and below). The challenges posed by genome data—intertwined scale levels, persistent elements across scales, detailed geometry for all scales, and closely spaced conceptual scales—require a novel approach.

Key Features:

- Scale-Dependent Camera Model: Controls visual embedding of scales into their parents, rendering relevant subsets, and adjusting view location, size, and scope.
- Visual Embedding: Seamlessly integrates larger-scale elements while adding details from lower-scale levels, enabling smooth transitions between scales.
- Interactive Exploration: Supports interactive focus specification, visual highlighting, and scale manipulation for intuitive data navigation.

Applications:

- Enables understanding of DNA structure and organization at various scales.
- Facilitates exploration of correlations between spatial proximity of bases and genetic disorders.
- Aids in teaching and research by providing a comprehensive view of the genome's multi-scale complexity.

Unique Requirements:

Unlike other multi-scale domains, genome data:

- Has intertwined scale levels due to the DNA's connected nature.
- Does not lose elements as scales are zoomed out; instead, they group differently.
- Possesses detailed geometry for all scales, requiring efficient visual representation techniques.
- Has closely spaced conceptual scales, demanding effective visual embedding strategies.

Description

ScaleTrotter is an interactive multi-scale visualization tool for biological data, enabling users to explore genome details from nucleus to atomistic composition, bridging vast scales with seamless transitions. This framework overcomes unique challenges distinct from astronomical data visualization. It facilitates understanding of complex genomic structures through intuitive, interactive representations.

Technical Information

  • File Format: PDF
  • File Size: 14.28 MB
  • Pages: 11
  • Language: EN
  • Author: Sarkis Halladjian, Haichao Miao, David Kouril, M. Eduard Gröller, Ivan Viola, and Tobias Isenberg
  • Total Downloads: 54
  • Last Updated: 2 hours ago

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