ArticleBMC bioinformatics2017
A taxonomy of visualization tasks for the analysis of biological pathway data.
Article in BMC bioinformatics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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Who cites it
10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Toward Guidelines for Designing Holistic Integrated Information Visualizations for Time-Critical Contexts: Systematic Review.Journal of medical Internet research · 2024Pooled it
- WayFindR: investigating feedback in biological pathways.NAR genomics and bioinformatics · 2026Article
- Effective data visualization strategies in untargeted metabolomics.Natural product reports · 2025Review
- Towards a hybrid user interface for the visual exploration of large biomolecular networks using virtual reality.Journal of integrative bioinformatics · 2022Article
- Uncertainty Visualization: Concepts, Methods, and Applications in Biological Data Visualization.Frontiers in bioinformatics · 2022Review
- Article
- Metabopolis: scalable network layout for biological pathway diagrams in urban map style.BMC bioinformatics · 2019Article
- Integrating bioinformatics approaches for a comprehensive interpretation of metabolomics datasets.Current opinion in biotechnology · 2018Review
- The Kappa platform for rule-based modeling.Bioinformatics (Oxford, England) · 2018Article
- Challenges for visualizing three-dimensional data in genomic browsers.FEBS letters · 2017Review
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundUnderstanding complicated networks of interactions and chemical components is essential to solving contemporary problems in modern biology, especially in domains such as cancer and systems research. In these domains, biological pathway data is used to represent chains of interactions that occur within a given biological process. Visual representations can help researchers understand, interact with, and reason about these complex pathways in a number of ways. At the same time, these datasets offer unique challenges for visualization, due to their complexity and heterogeneity.
resultsHere, we present taxonomy of tasks that are regularly performed by researchers who work with biological pathway data. The generation of these tasks was done in conjunction with interviews with several domain experts in biology. These tasks require further classification than is provided by existing taxonomies. We also examine existing visualization techniques that support each task, and we discuss gaps in the existing visualization space revealed by our taxonomy.
conclusionsOur taxonomy is designed to support the development and design of future biological pathway visualization applications. We conclude by suggesting future research directions based on our taxonomy and motivated by the comments received by our domain experts.
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