Unfolding Ordered Matrices into BioFabric Motifs

Fuente: arXiv
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Main Authors: Wulms, Jules, Meulemans, Wouter, Speckmann, Bettina
Format: Preprint
Published: 2026
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author Wulms, Jules
Meulemans, Wouter
Speckmann, Bettina
author_facet Wulms, Jules
Meulemans, Wouter
Speckmann, Bettina
contents BioFabrics were introduced by Longabaugh in 2012 as a way to draw large graphs in a clear and uncluttered manner. The visual quality of BioFabrics crucially depends on the order of vertices and edges, which can be chosen independently. Effective orders can expose salient patterns, which in turn can be summarized by motifs, allowing users to take in complex networks at-a-glance. However, so far there is no efficient layout algorithm which automatically recognizes patterns and delivers both a vertex and an edge ordering that allows these patterns to be expressed as motifs. In this paper we show how to use well-ordered matrices as a tool to efficiently find good vertex and edge orders for BioFabrics. Specifically, we order the adjacency matrix of the input graph using Moran's $I$ and detect (noisy) patterns with our recent algorithm. In this note we show how to "unfold" the ordered matrix and its patterns into a high-quality BioFabric. Our pipelines easily handles graphs with up to 250 vertices.
format Preprint
id arxiv_https___arxiv_org_abs_2602_19745
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Unfolding Ordered Matrices into BioFabric Motifs
Wulms, Jules
Meulemans, Wouter
Speckmann, Bettina
Human-Computer Interaction
BioFabrics were introduced by Longabaugh in 2012 as a way to draw large graphs in a clear and uncluttered manner. The visual quality of BioFabrics crucially depends on the order of vertices and edges, which can be chosen independently. Effective orders can expose salient patterns, which in turn can be summarized by motifs, allowing users to take in complex networks at-a-glance. However, so far there is no efficient layout algorithm which automatically recognizes patterns and delivers both a vertex and an edge ordering that allows these patterns to be expressed as motifs. In this paper we show how to use well-ordered matrices as a tool to efficiently find good vertex and edge orders for BioFabrics. Specifically, we order the adjacency matrix of the input graph using Moran's $I$ and detect (noisy) patterns with our recent algorithm. In this note we show how to "unfold" the ordered matrix and its patterns into a high-quality BioFabric. Our pipelines easily handles graphs with up to 250 vertices.
title Unfolding Ordered Matrices into BioFabric Motifs
topic Human-Computer Interaction
url https://arxiv.org/abs/2602.19745