Optimizing Staircase Motifs in Biofabric Network Layouts

Abstract Biofabric is a novel method for network visualization, with promising potential to highlight specific network features. Recent studies emphasize the importance of staircase motifs — equivalent to fans or stars in node‐link diagrams — within Biofabric. However, to effectively showcase these motifs, we need to formulate specialized layout algorithms. This paper introduces a method to compute optimal layouts for Biofabric, focusing on maximizing staircase formation. We present an Integer Linear Programming (ILP) model for this task and evaluate its performance in terms of scalability and output quality against a leading heuristic method, Degreecending. Our results demonstrate that the ILP approach identifies significantly more, and often longer, staircases compared to Degreecending, albeit with the trade‐off of higher computation times. Our supplemental material, including a full copy of the paper, code, and results, is available on osf.io.

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Publication Details

Journal
Computer Graphics Forum
Published
2025-05-23
DOI
https://doi.org/10.1111/cgf.70139
Citations
1
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
1.28

Funders

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article

Optimizing Staircase Motifs in Biofabric Network Layouts

Markus Wallinger, Sara Di Bartolomeo, Martin Nöllenburg
1 citations
Computer Graphics Forum
Data Visualization and Analytics
1.28
article

Optimizing Staircase Motifs in Biofabric Network Layouts

Markus Wallinger, Sara Di Bartolomeo, Martin Nöllenburg
article en
1 citations

Abstract

Abstract Biofabric is a novel method for network visualization, with promising potential to highlight specific network features. Recent studies emphasize the importance of staircase motifs — equivalent to fans or stars in node‐link diagrams — within Biofabric. However, to effectively showcase these motifs, we need to formulate specialized layout algorithms. This paper introduces a method to compute optimal layouts for Biofabric, focusing on maximizing staircase formation. We present an Integer Linear Programming (ILP) model for this task and evaluate its performance in terms of scalability and output quality against a leading heuristic method, Degreecending. Our results demonstrate that the ILP approach identifies significantly more, and often longer, staircases compared to Degreecending, albeit with the trade‐off of higher computation times. Our supplemental material, including a full copy of the paper, code, and results, is available on osf.io.

Computer Graphics ForumVol. 44(3)
TU Wien (AT), Technical University of Munich (DE)
Technische Universitat Wien, Austrian Science Fund
Openalex Percentile: Top 20%
Data Visualization and Analytics
1.28
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Optimizing Staircase Motifs in Biofabric Network Layouts — Markus Wallinger, Sara Di Bartolomeo, et al. · Computer Graphics Forum (2025) | TGRS Research Map | TGRS