ArticleBMC proceedings2015
ReactionFlow: an interactive visualization tool for causality analysis in biological pathways.
Article in BMC proceedings, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Article
- The Kappa platform for rule-based modeling.Bioinformatics (Oxford, England) · 2018Article
- CellNetVis: a web tool for visualization of biological networks using force-directed layout constrained by cellular components.BMC bioinformatics · 2017Article
- A taxonomy of visualization tasks for the analysis of biological pathway data.BMC bioinformatics · 2017Article
- Highlights from the 5th Symposium on Biological Data Visualization: Part 2.BMC proceedings · 2015Article
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4 authors.
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Abstract
backgroundMolecular and systems biologists are tasked with the comprehension and analysis of incredibly complex networks of biochemical interactions, called pathways, that occur within a cell. Through interviews with domain experts, we identified four common tasks that require an understanding of the causality within pathways, that is, the downstream and upstream relationships between proteins and biochemical reactions, including: visualizing downstream consequences of perturbing a protein; finding the shortest path between two proteins; detecting feedback loops within the pathway; and identifying common downstream elements from two or more proteins.
resultsWe introduce ReactionFlow, a visual analytics application for pathway analysis that emphasizes the structural and causal relationships amongst proteins, complexes, and biochemical reactions within a given pathway. To support the identified causality analysis tasks, user interactions allow an analyst to filter, cluster, and select pathway components across linked views. Animation is used to highlight the flow of activity through a pathway.
conclusionsWe evaluated ReactionFlow by providing our application to two domain experts who have significant experience with biomolecular pathways, after which we conducted a series of in-depth interviews focused on each of the four causality analysis tasks. Their feedback leads us to believe that our techniques could be useful to researchers who must be able to understand and analyze the complex nature of biological pathways. ReactionFlow is available at https://github.com/CreativeCodingLab/ReactionFlow.
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