PathRings: a web-based tool for exploration of ortholog and expression data in biological pathways

Author(s)Zhu, Yongnan
Author(s)Sun, Liang
Author(s)Garbarino, Alexander
Author(s)Schmidt, Carl
Author(s)Fang, Jinglong
Author(s)Chen, Jian
Ordered AuthorYongnan Zhu, Liang Sun, Alexander Garbarino, Carl Schmidt, Jinglong Fang and Jian Chen
UD AuthorSun, Liangen_US
UD AuthorSchmidt, Carl
Date Accessioned2015-12-09T14:59:43Z
Date Available2015-12-09T14:59:43Z
Copyright DateCopyright ©2015 Zhu et al.en_US
Publication Date2015-05-19
DescriptionPublisher's PDFen_US
AbstractBackground High-throughput methods are generating biological data on a vast scale. In many instances, genomic, transcriptomic, and proteomic data must be interpreted in the context of signaling and metabolic pathways to yield testable hypotheses. Since humans can interpret visual information rapidly, a means for interactive visual exploration that lets biologists interpret such data in a comprehensive and exploratory manner would be invaluable. However, humans have limited memory capacity. Current visualization tools have limited viewing and manipulation capabilities to address complex data analysis problems, and visual exploratory tools are needed to reduce the high mental workload imposed on biologists. Results We present PathRings, a new interactive web-based, scalable biological pathway visualization tool for biologists to explore and interpret biological pathways. PathRings integrates metabolic and signaling pathways from Reactome in a single compound graph visualization, and uses color to highlight genes and pathways affected by input data. Pathways are available for multiple species and analysis of user-defined species or input is also possible. PathRings permits an overview of the impact of gene expression data on all pathways to facilitate visual pattern finding. Detailed pathways information can be opened in new visualizations while maintaining the overview, that form a visual exploration provenance. A dynamic multi-view bubbles interface is designed to support biologists’ analytical tasks by letting users construct incremental views that further reflect biologists’ analytical process. This approach decomposes complex tasks into simpler ones and automates multi-view management. Conclusions PathRings has been designed to accommodate interactive visual analysis of experimental data in the context of pathways defined by Reactome. Our new approach to interface design can effectively support comparative tasks over substantially larger collection than existing tools. The dynamic interaction among multi-view dataset visualization improves the data exploration. PathRings is available free at http://raven.anr.udel.edu/~sunliang/PathRings webcite and the source code is hosted on Github: https://github.com/ivcl/PathRings webcite.en_US
DepartmentUniversity of Delaware. Department of Animal and Food Sciences.en_US
CitationZhu et al. BMC Bioinformatics (2015) 16:165 DOI 10.1186/s12859-015-0585-1en_US
DOI10.1186/s12859-015-0585-1en_US
ISSN1471-2105en_US
URLhttp://udspace.udel.edu/handle/19716/17287
Languageen_USen_US
PublisherBioMed Central Ltd.en_US
dc.rightsCC-BY 4.0en_US
dc.sourceBMC Bioinformaticsen_US
dc.source.urihttp://www.biomedcentral.com/bmcbioinformatics/en_US
TitlePathRings: a web-based tool for exploration of ortholog and expression data in biological pathwaysen_US
TypeArticleen_US
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