ReactionFlow: an interactive visualization tool for causality analysis in biological pathways

BMC Proceedings

Research

Angus Graeme Forbes¹  Paul Murray¹  Jillian Aurisano¹  Tuan Nhon Dang¹ 

[1] Department of Computer Science M/C 152, University of Illinois at Chicago, 851 S. Morgan, Room 1120, 60607-7053, Chicago, IL, USA;

关键词: Pathway visualization;    Biological networks;    Causality analysis;    Topological ordering;   

DOI  :  10.1186/1753-6561-9-S6-S6

来源: Springer

【 摘 要 】

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.

【 授权许可】

Unknown   
© Dang et al. 2015. This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.