Visualizing Related Metabolic Pathways in Two and a Half Dimensions

Brandes, Ulrik; Dwyer, Tim; Schreiber, Falk

doi:10.1007/978-3-540-24595-7_10

Cited by 36 publications

(38 citation statements)

References 23 publications

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“…In a similar manner to "camouflage breaking," our technique incorporates stereoscopy to isolate subsets of a 2D graph as a separate layer, and thus create 2.5D layouts. There are many examples of 2.5D graph layouts where the third dimension is exploited to encode aspects of the data other than the relations among nodes [26]. For example, in [28] the third dimension is used to encode a hierarchical nesting of clusters in the graph via overlaid transparent layers.…”

Section: Related Workmentioning

confidence: 99%

Stereoscopic Highlighting: 2D Graph Visualization on Stereo Displays

Alper

Höllerer

Kuchera-Morin

et al. 2011

IEEE Trans. Visual. Comput. Graphics

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Fig. 1. The stereoscopic highlighting technique illustrated with separate images for the left and right eye. The highlighted yellow node and all of its immediate neighbors are rendered at a depth closer to the viewer. The two images above represent a stereo pair. By crossing eyes, the reader can perceive the 3rd dimension of the stereoscopic highlighting.Abstract-In this paper we present a new technique and prototype graph visualization system, stereoscopic highlighting, to help answer accessibility and adjacency queries when interacting with a node-link diagram. Our technique utilizes stereoscopic depth to highlight regions of interest in a 2D graph by projecting these parts onto a plane closer to the viewpoint of the user. This technique aims to isolate and magnify specific portions of the graph that need to be explored in detail without resorting to other highlighting techniques like color or motion, which can then be reserved to encode other data attributes. This mechanism of stereoscopic highlighting also enables focus+context views by juxtaposing a detailed image of a region of interest with the overall graph, which is visualized at a further depth with correspondingly less detail. In order to validate our technique, we ran a controlled experiment with 16 subjects comparing static visual highlighting to stereoscopic highlighting on 2D and 3D graph layouts for a range of tasks. Our results show that while for most tasks the difference in performance between stereoscopic highlighting alone and static visual highlighting is not statistically significant, users performed better when both highlighting methods were used concurrently. In more complicated tasks, 3D layout with static visual highlighting outperformed 2D layouts with a single highlighting method. However, it did not outperform the 2D layout utilizing both highlighting techniques simultaneously. Based on these results, we conclude that stereoscopic highlighting is a promising technique that can significantly enhance graph visualizations for certain use cases.

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Section: Related Workmentioning

confidence: 99%

Stereoscopic Highlighting: 2D Graph Visualization on Stereo Displays

Alper

Höllerer

Kuchera-Morin

et al. 2011

IEEE Trans. Visual. Comput. Graphics

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“…An example is the Caleydo framework [21] that extends the standard pathways of KEGG into 2.5D, similar to the report of Kerren [12] and the work of Brandes et al [15], combined with brushing, highlighting, focus&context, and detail on demand. In this way, it supports the interactive exploration and navigation between several interconnected (but static!)…”

Section: Related Workmentioning

confidence: 98%

A Novel Grid-Based Visualization Approach for Metabolic Networks with Advanced Focus&Context View

Rohrschneider

Heine

Reichenbach

et al. 2010

Lecture Notes in Computer Science

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Abstract. The universe of biochemical reactions in metabolic pathways can be modeled as a complex network structure augmented with domain specific annotations. Based on the functional properties of the involved reactions, metabolic networks are often clustered into so-called pathways inferred from expert knowledge. To support the domain expert in the exploration and analysis process, we follow the well-known Table Lens metaphor with the possibility to select multiple foci.In this paper, we introduce a novel approach to generate an interactive layout of such a metabolic network taking its hierarchical structure into account and present methods for navigation and exploration that preserve the mental map. The layout places the network nodes on a fixed rectilinear grid and routes the edges orthogonally between the node positions. Our approach supports bundled edge routes heuristically minimizing a given cost function based on the number of bends, the number of edge crossings and the density of edges within a bundle.

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“…, k) such that the coordinates of all nodes common to two or more subgraphs are the same. An alternative representation has been given in [4] where the third dimension has been used to stack the k layouts above each other. In these layouts, crossings between edges belonging to different graphs G i = G j are either completely ignored or counted as less important than "real" crossings.…”

Section: Visual Comparison Of Similar Biological Networkmentioning

confidence: 99%

On Open Problems in Biological Network Visualization

Albrecht

Kerren

Klein

et al. 2010

Lecture Notes in Computer Science

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Abstract. Much of the data generated and analyzed in the life sciences can be interpreted and represented by networks or graphs. Network analysis and visualization methods help in investigating them, and many universal as well as specialpurpose tools and libraries are available for this task. However, the two fields of graph drawing and network biology are still largely disconnected. Hence, visualization of biological networks does typically not apply state-of-the-art graph drawing techniques, and graph drawing tools do not respect the drawing conventions of the life science community.In this paper, we analyze some of the major problems arising in biological network visualization. We characterize these problems and formulate a series of open graph drawing problems. These use cases illustrate the need for efficient algorithms to present, explore, evaluate, and compare biological network data. For each use case, problems are discussed and possible solutions suggested.

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Visualizing Related Metabolic Pathways in Two and a Half Dimensions

Cited by 36 publications

References 23 publications

Stereoscopic Highlighting: 2D Graph Visualization on Stereo Displays

Stereoscopic Highlighting: 2D Graph Visualization on Stereo Displays

A Novel Grid-Based Visualization Approach for Metabolic Networks with Advanced Focus&Context View

On Open Problems in Biological Network Visualization

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